Estimation of theWeibull Tail Coefficient Through the Power Mean-of-Order- p

被引:1
作者
Caeiro, Frederico [1 ,2 ]
Gomes, M. Ivette [3 ,4 ]
Henriques-Rodrigues, Ligia [5 ,6 ]
机构
[1] NOVA Univ Lisbon, NOVA Sch Sci & Technol FCT NOVA, Campus Caparica, Lisbon, Portugal
[2] NOVA Univ Lisbon, CMA, Campus Caparica, Lisbon, Portugal
[3] Univ Lisbon, Fac Sci Lisbon FCUL DEIO, Lisbon, Portugal
[4] Univ Lisbon, CEAUL, Lisbon, Portugal
[5] Univ Evora, Sch Sci & Technol ECT UE, Evora, Portugal
[6] Univ Evora, CIMA, Evora, Portugal
来源
RECENT DEVELOPMENTS IN STATISTICS AND DATA SCIENCE, SPE2021 | 2022年 / 398卷
关键词
Power mean-of-order-p; Semi-parametric estimation; Statistics of extremes; Weibull tail coefficient; EXTREME-VALUE THEORY; INFERENCE; HILL;
D O I
10.1007/978-3-031-12766-3_4
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Weibull tail coefficient (WTC) is the parameter. in a right-tail function of the type (F) over bar := 1 - F, such that H := - ln (F) over bar is a regularly varying function at infinity with an index of regular variation equal to theta is an element of R+. In a context of extreme value theory for maxima, it is possible to prove that we have an extreme value index (EVI)xi = 0, but usually a very slow rate of convergence. Most of the recent WTCestimators are proportional to the class of Hill EVI-estimators, the average of the log-excesses associated with the k upper order statistics, 1 <= k < n. The interesting performance of EVI-estimators based on generalized means leads us to base theWTC-estimation on the power mean-of-order- p (MOp) EVI-estimators. Consistency of the WTC-estimators is discussed and their performance, for finite samples, is illustrated through a small-scale Monte Carlo simulation study.
引用
收藏
页码:41 / 53
页数:13
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