Automated threshold selection for extreme value analysis via ordered goodness-of-fit tests with adjustment for false discovery rate

DOI10.1214/17-aoas1092zbMath1393.62023arXiv1604.02024OpenAlexW2790880830MaRDI QIDQ133065

Brian Bader, Xuebin Zhang, Jun Yan, Jun Yan, Xuebin Zhang, Brian Bader

Publication date: 1 March 2018

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1604.02024

zbMATH Keywords

stopping rulespecification testbatch analysisexceedance diagnostic

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Statistics of extreme values; tail inference (62G32) Paired and multiple comparisons; multiple testing (62J15)

Related Items (13)

Discussion of ‘On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures’ ⋮ Threshold selection in univariate extreme value analysis ⋮ Estimation for Extreme Conditional Quantiles of Functional Quantile Regression ⋮ Extreme tail risk estimation with the generalized Pareto distribution under the peaks-over-threshold framework ⋮ POT-based estimator of the ruin probability in infinite time for loss models: An application to insurance risk ⋮ A modeler's guide to extreme value software ⋮ Invited article by M. Gidea: Extreme events and emergency scales ⋮ Threshold selection and trimming in extremes ⋮ Automated threshold selection for extreme value analysis via ordered goodness-of-fit tests with adjustment for false discovery rate ⋮ eva ⋮ The risk function of the goodness-of-fit tests for tail models ⋮ Multifractal characteristics on multiple pollution variables in Malaysia ⋮ Scoring predictions at extreme quantiles

Uses Software

• ismev
• texmex
• eva

Cites Work

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