A Class of Semiparametric Tail Index Estimators and Its Applications

M. Vaičiulis; N. M. Markovich

doi:10.1134/S0005117919100035

A Class of Semiparametric Tail Index Estimators and Its Applications

M. Vaičiulis
, N. M. Markovich

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

A new class of semiparametric estimators of the tail index is proposed. These estimators are based on a rather general class of semiparametric statistics. Their asymptotic normality is proved. The new estimators are compared with several other recently introduced estimators of the tail index in terms of the asymptotic mean-square error. An algorithm to calculate the new estimators is developed and then applied to several real data sets.

Original language	English
Pages (from-to)	1803-1816
Number of pages	14
Journal	Automation and Remote Control
Volume	80
Issue number	10
DOIs	https://doi.org/10.1134/S0005117919100035
State	Published - 1 Oct 2019
Externally published	Yes

Keywords

Hill’s estimator
asymptotic mean-square error
normal distribution
tail index

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1134/S0005117919100035

Cite this

@article{10b48d47b3f24fa7be13079d22026ba4,

title = "A Class of Semiparametric Tail Index Estimators and Its Applications",

abstract = "A new class of semiparametric estimators of the tail index is proposed. These estimators are based on a rather general class of semiparametric statistics. Their asymptotic normality is proved. The new estimators are compared with several other recently introduced estimators of the tail index in terms of the asymptotic mean-square error. An algorithm to calculate the new estimators is developed and then applied to several real data sets.",

keywords = "Hill{\textquoteright}s estimator, asymptotic mean-square error, normal distribution, tail index",

author = "M. Vai{\v c}iulis and Markovich, \{N. M.\}",

note = "Publisher Copyright: {\textcopyright} 2019, Pleiades Publishing, Ltd.",

year = "2019",

month = oct,

day = "1",

doi = "10.1134/S0005117919100035",

language = "English",

volume = "80",

pages = "1803--1816",

journal = "Automation and Remote Control",

issn = "0005-1179",

publisher = "Pleiades Publishing",

number = "10",

}

TY - JOUR

T1 - A Class of Semiparametric Tail Index Estimators and Its Applications

AU - Vaičiulis, M.

AU - Markovich, N. M.

PY - 2019/10/1

Y1 - 2019/10/1

N2 - A new class of semiparametric estimators of the tail index is proposed. These estimators are based on a rather general class of semiparametric statistics. Their asymptotic normality is proved. The new estimators are compared with several other recently introduced estimators of the tail index in terms of the asymptotic mean-square error. An algorithm to calculate the new estimators is developed and then applied to several real data sets.

AB - A new class of semiparametric estimators of the tail index is proposed. These estimators are based on a rather general class of semiparametric statistics. Their asymptotic normality is proved. The new estimators are compared with several other recently introduced estimators of the tail index in terms of the asymptotic mean-square error. An algorithm to calculate the new estimators is developed and then applied to several real data sets.

KW - Hill’s estimator

KW - asymptotic mean-square error

KW - normal distribution

KW - tail index

UR - https://www.scopus.com/pages/publications/85073624855

U2 - 10.1134/S0005117919100035

DO - 10.1134/S0005117919100035

M3 - Article

AN - SCOPUS:85073624855

SN - 0005-1179

VL - 80

SP - 1803

EP - 1816

JO - Automation and Remote Control

JF - Automation and Remote Control

IS - 10

ER -

A Class of Semiparametric Tail Index Estimators and Its Applications

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this