A robust prediction error criterion for pareto modelling of upper tails

DOI10.1002/cjs.5550340406zbMath1115.62056OpenAlexW3123351385MaRDI QIDQ5295957

Maria-Pia Victoria-Feser, Debbie J. Dupuis

Publication date: 31 July 2007

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.5550340406

zbMATH Keywords

robustnessincome distributiontail indexregressionvalue at riskextreme valueM-estimatorPareto model

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Robustness and adaptive procedures (parametric inference) (62F35) Statistics of extreme values; tail inference (62G32)

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Evaluation of robust outlier detection methods for zero-inflated complex data ⋮ A robust semi-parametric approach for measuring income inequality in Malaysia ⋮ Weak properties and robustness of t-Hill estimators ⋮ Asymptotic and bootstrap inference for top income shares ⋮ A review of more than one hundred Pareto-tail index estimators ⋮ A robust coefficient of determination for regression ⋮ Data-adaptive trimming of the Hill estimator and detection of outliers in the extremes of heavy-tailed data ⋮ Zero-inflated truncated generalized Pareto distribution for the analysis of radio audience data ⋮ Detecting influential data points for the Hill estimator in Pareto-type distributions ⋮ Robust fitting of claim severity distributions and the method of trimmed moments ⋮ Optimally robust estimators in generalized Pareto models ⋮ Robust and Efficient Fitting of Loss Models

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