On a Minimum Distance Procedure for Threshold Selection in Tail Analysis

DOI10.1137/19M1260463zbMath1484.62057arXiv1811.06433OpenAlexW3103238892MaRDI QIDQ5027018

Anja Janssen, Tiandong Wang, Holger Drees, Sidney I. Resnick

Publication date: 3 February 2022

Published in: SIAM Journal on Mathematics of Data Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1811.06433

zbMATH Keywords

empirical processespower lawsthreshold selectionpreferential attachmentHill estimators

Mathematics Subject Classification ID

Gaussian processes (60G15) Asymptotic distribution theory in statistics (62E20) Random graphs (graph-theoretic aspects) (05C80) Order statistics; empirical distribution functions (62G30) Extreme value theory; extremal stochastic processes (60G70) Statistics of extreme values; tail inference (62G32)

Related Items (7)

Randomly stopped extreme Zipf extensions ⋮ Consistency of Hill estimators in a linear preferential attachment model ⋮ Gradient boosting for extreme quantile regression ⋮ Poisson edge growth and preferential attachment networks ⋮ Threshold selection and trimming in extremes ⋮ Are extreme value estimation methods useful for network data? ⋮ Large degrees in scale-free inhomogeneous random graphs

Uses Software

• ismev
• KONECT
• poweRlaw
• GitHub
• plfit

Cites Work

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