Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions

被引：1

作者：

Ahmad, Aboubacrene Ag ^{[1
]}

Deme, El Hadji ^{[1
]}

Diop, Moo ^{[1
]}

Girard, Stephane ^{[2
]}

机构：

[1] Univ Gaston Berger, LERSTAD, UFR SAT, BP 234, St Louis, Senegal

[2] Univ Grenoble Alpes, INRIA, CNRS, Grenoble INP,LJK, F-38000 Grenoble, France

来源：

DEPENDENCE MODELING | 2019年 / 7卷 / 01期

关键词：

Nonparametric estimation; location-scale function; tail-index; extreme-values; conditional quantile; EXTREME-VALUE INDEX; NONPARAMETRIC-ESTIMATION; REGRESSION; MODELS;

D O I：

10.1515/demo-2019-0021

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We introduce a location-scale model for conditional heavy-tailed distributions when the covariate is deterministic. First, nonparametric estimators of the location and scale functions are introduced. Second, an estimator of the conditional extreme-value index is derived. The asymptotic properties of the estimators are established under mild assumptions and their finite sample properties are illustrated both on simulated and real data.

引用

页码：394 / 417

页数：24

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