Discussion on paper ‘On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures’ by Zhengjun Zhang

IF 0.7 Q3 STATISTICS & PROBABILITY Statistical Theory and Related Fields Pub Date : 2021-01-02 DOI:10.1080/24754269.2020.1862589
Y. Qi
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引用次数: 1

Abstract

I would like to take this opportunity to congratulate Zhengjun for his continuing contribution to extremevalue statistics in recent years. In this review paper, some fundamental theories on univariate extremes and multivariate extremes are introduced, and recent developments on extremes from some structured stochastic processes are also given. The results in the latter sections of the paper are largely due to Zhengjun and his coauthors. The paper provides some insights for future challenges on extremes and can help young researchers follow the contemporary research topics. Below I offer some comments onunivariate extremevalue statistics. Although the theory for univariate extremes is quite complete, the statistical methods such as the estimation and inference procedures are far from perfect. Set μ = 0 and σ = 1 in the definition (2.6) in the paper and write
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对张正军《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》一文的讨论
我想借此机会祝贺郑军近年来对极值统计的持续贡献。本文介绍了单变量极值和多变量极值的一些基本理论,并给出了一些结构化随机过程极值的最新进展。论文后面部分的结果主要归功于郑军和他的合著者。这篇论文为未来的极端挑战提供了一些见解,可以帮助年轻的研究人员关注当代的研究主题。下面我对多变量极值统计提出一些看法。尽管单变量极值的理论相当完整,但估计和推理程序等统计方法还远远不够完善。在论文中的定义(2.6)中设置μ=0和σ=1,并写入
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来源期刊
CiteScore
0.90
自引率
20.00%
发文量
21
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