On the estimation of the Weibull tail coefficient

DOI10.1016/0378-3758(93)90022-XzbMath0771.62026OpenAlexW2003876810MaRDI QIDQ2366576

Michel Broniatowski

Publication date: 30 August 1993

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(93)90022-x

zbMATH Keywords

consistencyasymptotic normalitysimulation resultsempirical processWeibull distributionquantile processparametric estimationtail estimationWeibull tail coefficientestimation of regular variation indexweighted average of upper order statistics

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Order statistics; empirical distribution functions (62G30)

Related Items (19)

On the estimation of the functional Weibull tail-coefficient ⋮ A Hill Type Estimator of the Weibull Tail-Coefficient ⋮ Kernel regression with Weibull-type tails ⋮ On tests to distinguish distribution tails invariant with respect to the scale parameter ⋮ Approximation of high quantiles from intermediate quantiles ⋮ Approximation and estimation of very small probabilities of multivariate extreme events ⋮ Estimation of extreme quantiles from heavy and light tailed distributions ⋮ Extremal linear quantile regression with Weibull-type tails ⋮ Bias-reduced extreme quantile estimators of Weibull tail-distributions ⋮ Estimation of the Weibull tail-coefficient with linear combination of upper order statistics ⋮ Weibull tail-distributions revisited: A new look at some tail estimators ⋮ Goodness-of-fit testing for Weibull-type behavior ⋮ Estimating Extreme Quantiles of Weibull Tail Distributions ⋮ Generalized Kernel Estimators for the Weibull-Tail Coefficient ⋮ Bias-reduced estimators of the Weibull tail-coefficient ⋮ A Beran-inspired estimator for the Weibull-type tail coefficient ⋮ Estimation of distribution tails —a semiparametric approach ⋮ Robust conditional Weibull-type estimation ⋮ A weighted mean excess function approach to the estimation of Weibull-type tails

Uses Software

• AS 70

Cites Work

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• A moment estimator for the index of an extreme-value distribution
• Kernel estimates of the tail index of a distribution
• Weighted empirical and quantile processes
• On the influence of the extremes of an i.i.d. sequence on the maximal spacings
• Adaptive estimates of parameters of regular variation
• On the relative stability of large order statistics
• On record values and the exponent of a distribution with regularly varying upper tail
• Limit theorems for the ratio of the empirical distribution function to the true distribution function

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