Cluster based inference for extremes of time series
Statistics Theory
2021-03-16 v1 Methodology
Statistics Theory
Abstract
We introduce a new type of estimator for the spectral tail process of a regularly varying time series. The approach is based on a characterizing invariance property of the spectral tail process, which is incorporated into the new estimator via a projection technique. We show uniform asymptotic normality of this estimator, both in the case of known and of unknown index of regular variation. In a simulation study the new procedure shows a more stable performance than previously proposed estimators.
Cite
@article{arxiv.2103.08512,
title = {Cluster based inference for extremes of time series},
author = {Holger Drees and Anja Janßen and Sebastian Neblung},
journal= {arXiv preprint arXiv:2103.08512},
year = {2021}
}