Uniqueness and global optimality of the maximum likelihood estimator for the generalized extreme value distribution

Uniqueness and global optimality of the maximum likelihood estimator for the generalized extreme value distribution
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广义极值分布最大似然估计的唯一性和全局最优性

DOI:
10.1093/biomet/asab043
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发表时间:
2021
期刊:
影响因子:
2.7
通讯作者:
Shaby, Benjamin A
Shaby, Benjamin A
中科院分区:
数学2区
文献类型:
--
作者:
Zhang, Likun;Shaby, Benjamin A

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三参数广义极值分布起源于经典的单变量极值理论,通常用于分析观测现象的远尾,但在该标准模型下,基于似然估计的重要渐近性质尚未建立。本文证明了极大似然估计量是全局唯一的。一个有趣的次要结果包含了在真形参数的紧邻域中一类极限关系的一致一致性。
The three-parameter generalized extreme value distribution arises from classical univariate extreme value theory, and is in common use for analysing the far tail of observed phenomena, yet important asymptotic properties of likelihood-based estimation under this standard model have not been established. In this paper we prove that the maximum likelihood estimator is global and unique. An interesting secondary result entails the uniform consistency of a class of limit relations in a tight neighbourhood of the true shape parameter.
DOI: 10.3150/13-bej573
发表时间: 2015-02-01
期刊: BERNOULLI
影响因子: 1.5
作者:
Dombry, Clement
通讯作者: Dombry, Clement
DOI: 10.1007/s10687-017-0292-6
发表时间: 2017-12-01
期刊: EXTREMES
影响因子: 1.3
作者:
Buecher, Axel;Segers, Johan
通讯作者: Segers, Johan