Discussion of ‘On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures’

IF 0.7 Q3 STATISTICS & PROBABILITY Statistical Theory and Related Fields Pub Date : 2021-01-02 DOI:10.1080/24754269.2020.1869897
Tiandong Wang, Jun Yan
{"title":"Discussion of ‘On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures’","authors":"Tiandong Wang, Jun Yan","doi":"10.1080/24754269.2020.1869897","DOIUrl":null,"url":null,"abstract":"We congratulate Prof. Zhang for this timely review on recent advances in extreme value theory for heterogeneous populations and on time series models for extreme observations. This is a substantial effort. Not only does it give a summary of the state-of-the-art work in time series modelling of extremes but also suggests interesting methodological and applied research questions. Our discussion focuses on extremal dependence metrics and practical applications for the time series models.","PeriodicalId":22070,"journal":{"name":"Statistical Theory and Related Fields","volume":"5 1","pages":"38 - 40"},"PeriodicalIF":0.7000,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24754269.2020.1869897","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistical Theory and Related Fields","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1080/24754269.2020.1869897","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: 0

Abstract

We congratulate Prof. Zhang for this timely review on recent advances in extreme value theory for heterogeneous populations and on time series models for extreme observations. This is a substantial effort. Not only does it give a summary of the state-of-the-art work in time series modelling of extremes but also suggests interesting methodological and applied research questions. Our discussion focuses on extremal dependence metrics and practical applications for the time series models.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
关于“用非线性时间序列模型和尾部相关测度研究极值和系统风险”的讨论
我们祝贺张教授及时回顾了异质性种群极值理论和极值观测时间序列模型的最新进展。这是一项实质性的努力。它不仅总结了极端时间序列建模的最新研究成果,而且还提出了有趣的方法和应用研究问题。我们的讨论重点是时间序列模型的极端依赖度量和实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
0.90
自引率
20.00%
发文量
21
期刊最新文献
Multiply robust estimation for average treatment effect among treated Communication-efficient distributed statistical inference on zero-inflated Poisson models FragmGAN: generative adversarial nets for fragmentary data imputation and prediction Log-rank and stratified log-rank tests Autoregressive moving average model for matrix time series
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1