A heuristic adaptive choice of the threshold for bias-corrected Hill estimators

DOI10.1080/10629360600954000zbMath1136.62346OpenAlexW2147653081MaRDI QIDQ5457930

Clara Viseu, B. Vandewalle, M. Ivette Gomes, Ligia M. C. S. Rodrigues

Publication date: 10 April 2008

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10629360600954000

zbMATH Keywords

tablesheavy tailsextreme value indexstatistics of extremessemi-parametric estimationadaptive threshold choice

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistics of extreme values; tail inference (62G32) Monte Carlo methods (65C05)

Related Items (7)

Extreme Value Theory and Statistics of Univariate Extremes: A Review ⋮ POT-based estimator of the ruin probability in infinite time for loss models: An application to insurance risk ⋮ PORT Hill and Moment Estimators for Heavy-Tailed Models ⋮ Improved reduced-bias tail index and quantile estimators ⋮ Tail index and second-order parameters’ semi-parametric estimation based on the log-excesses ⋮ Tail index estimation for heavy tails; accommodation of bias in the excesses over a high threshold ⋮ A note on the asymptotic variance at optimal levels of a bias-corrected Hill estimator

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• Alternatives to a semi-parametric estimator of parameters of rare events -- the jackknife methodology

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