Asymptotic Distribution of an Extreme Value Index estimator Based on the Scaled Log-spacings

Frederico Almeida Gião Gonçalves Caeiro

doi:10.1063/1.3637901

Asymptotic Distribution of an Extreme Value Index estimator Based on the Scaled Log-spacings

Frederico Almeida Gião Gonçalves Caeiro

DM - Departamento de Matemática

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

In this article we are interested in the semi‐parametric estimation of the extreme value index, one of the most important parameters in statistics of extremes. Under a general third order condition, we study the asymptotic distributional properties of a reduced‐bias extreme value index estimator, based on the scaled log‐spacings of the largest observations.

Original language	Unknown
Title of host publication	AIP Conference Proceedings
Pages	1467-1470
Volume	1389
DOIs	https://doi.org/10.1063/1.3637901
Publication status	Published - 1 Jan 2011
Event	Numerical Analysis and Applied Mathematics ICNAAM 2011 - Duration: 1 Jan 2011 → …

Conference

Conference	Numerical Analysis and Applied Mathematics ICNAAM 2011
Period	1/01/11 → …

Access to Document

10.1063/1.3637901

Cite this

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title = "Asymptotic Distribution of an Extreme Value Index estimator Based on the Scaled Log-spacings",

abstract = "In this article we are interested in the semi‐parametric estimation of the extreme value index, one of the most important parameters in statistics of extremes. Under a general third order condition, we study the asymptotic distributional properties of a reduced‐bias extreme value index estimator, based on the scaled log‐spacings of the largest observations.",

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AB - In this article we are interested in the semi‐parametric estimation of the extreme value index, one of the most important parameters in statistics of extremes. Under a general third order condition, we study the asymptotic distributional properties of a reduced‐bias extreme value index estimator, based on the scaled log‐spacings of the largest observations.

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