Adaptive estimation of heavy right tails: resampling-based methods in action

DOI10.1007/s10687-011-0146-6zbMath1329.62230OpenAlexW2010302823MaRDI QIDQ907363

M. Manuela Neves, Fernanda Figueiredo, M. Ivette Gomes

Publication date: 25 January 2016

Published in: Extremes (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10687-011-0146-6

zbMATH Keywords

semiparametric estimationstatistics of extremesresampling-based methodology

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Applications of statistics to environmental and related topics (62P12) Statistics of extreme values; tail inference (62G32) Monte Carlo methods (65C05)

Related Items (19)

Estimation for Extreme Conditional Quantiles of Functional Quantile Regression ⋮ New Reduced-bias Estimators of a Positive Extreme Value Index ⋮ A Mean-of-Order-$$p$$ Class of Value-at-Risk Estimators ⋮ Adaptive Choice and Resampling Techniques in Extremal Index Estimation ⋮ Corrected-Hill versus partially reduced-bias value-at-risk estimation ⋮ Extreme Value Theory and Statistics of Univariate Extremes: A Review ⋮ Sequential Monte Carlo samplers to fit and compare insurance loss models ⋮ Extreme-value based estimation of the conditional tail moment with application to reinsurance rating ⋮ Semi-parametric regression estimation of the tail index ⋮ Semi-parametric probability-weighted moments estimation revisited ⋮ Adaptive confidence intervals for the tail coefficient in a wide second order class of Pareto models ⋮ Heavy tailed capital incomes: Zenga index, statistical inference, and ECHP data analysis ⋮ Tail fitting for truncated and non-truncated Pareto-type distributions ⋮ On the measurement and treatment of extremes in time series ⋮ A location-invariant probability weighted moment estimation of the Extreme Value Index ⋮ Modeling extreme events: sample fraction adaptive choice in parameter estimation ⋮ Estimation of a scale second-order parameter related to the PORT methodology ⋮ Bootstrap and Other Resampling Methodologies in Statistics of Extremes ⋮ Lehmer's mean-of-order- p extreme value index estimation: a simulation study and applications

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