Robust estimations for the tail index of weibull-type distribution

Chengping Gong; Chengxiu Ling

doi:10.3390/risks6040119

Robust estimations for the tail index of weibull-type distribution

Chengping Gong, Chengxiu Ling^*

^*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

Based on suitable left-truncated or censored data, two flexible classes of M-estimations of Weibull tail coefficient are proposed with two additional parameters bounding the impact of extreme contamination. Asymptotic normality with √n-rate of convergence is obtained. Its robustness is discussed via its asymptotic relative efficiency and influence function. It is further demonstrated by a small scale of simulations and an empirical study on CRIX.

Original language	English
Article number	119
Journal	Risks
Volume	6
Issue number	4
DOIs	https://doi.org/10.3390/risks6040119
Publication status	Published - Dec 2018
Externally published	Yes

Keywords

Asymptotic relative efficiency
CRIX
Influence function
Robust
Weibull tail coefficient

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10.3390/risks6040119

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title = "Robust estimations for the tail index of weibull-type distribution",

abstract = "Based on suitable left-truncated or censored data, two flexible classes of M-estimations of Weibull tail coefficient are proposed with two additional parameters bounding the impact of extreme contamination. Asymptotic normality with √n-rate of convergence is obtained. Its robustness is discussed via its asymptotic relative efficiency and influence function. It is further demonstrated by a small scale of simulations and an empirical study on CRIX.",

keywords = "Asymptotic relative efficiency, CRIX, Influence function, Robust, Weibull tail coefficient",

author = "Chengping Gong and Chengxiu Ling",

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AU - Ling, Chengxiu

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AB - Based on suitable left-truncated or censored data, two flexible classes of M-estimations of Weibull tail coefficient are proposed with two additional parameters bounding the impact of extreme contamination. Asymptotic normality with √n-rate of convergence is obtained. Its robustness is discussed via its asymptotic relative efficiency and influence function. It is further demonstrated by a small scale of simulations and an empirical study on CRIX.

KW - Asymptotic relative efficiency

KW - CRIX

KW - Influence function

KW - Robust

KW - Weibull tail coefficient

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JF - Risks

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Robust estimations for the tail index of weibull-type distribution

Abstract

Keywords

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