Peak-over-threshold estimators for spectral tail processes: random vs deterministic thresholds

DOI10.1007/s10687-019-00367-xzbMath1447.62050arXiv1901.05501OpenAlexW3009500082MaRDI QIDQ2198603

Miran Knežević, Holger Drees

Publication date: 10 September 2020

Published in: Extremes (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1901.05501

zbMATH Keywords

regular variationheavy tailsthreshold selectionstationary time seriestail processspectral tail process

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nonparametric estimation (62G05) Inference from stochastic processes and spectral analysis (62M15) Statistics of extreme values; tail inference (62G32)

Related Items (6)

Statistical analysis for stationary time series at extreme levels: new estimators for the limiting cluster size distribution ⋮ Estimation of cluster functionals for regularly varying time series: runs estimators ⋮ Cluster based inference for extremes of time series ⋮ Asymptotics for sliding blocks estimators of rare events ⋮ Bootstrapping Hill estimator and tail array sums for regularly varying time series ⋮ Estimation of cluster functionals for regularly varying time series: sliding blocks estimators

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