4 papers
Central limit theory for serial tail dependence estimators in heavy-tailed long memory linear time series
Ioan Scheffel, Marco Oesting, Gilles Stupfler
We prove multiple central limit theorems for serial tail dependence estimators in heavy-tailed long memory linear time series. The main theoretical tools are two novel multivariate…
Asymptotic behavior of spatio-temporal point processes of exceedances
Carolin Forster, Marco Oesting
In this paper, we analyze the asymptotic behavior of the point process of exceedances in a spatio-temporal setting whose points are given by the rescaled occurrence times, the site…
Central limit theory for Peaks-over-Threshold partial sums of long memory linear time series
Ioan Scheffel, Marco Oesting, Gilles Stupfler
Over the last 30 years, extensive work has been devoted to developing central limit theory for partial sums of subordinated long memory linear time series. A much less studied prob…
Accuracy estimation of neural networks by extreme value theory
Gero Junike, Marco Oesting
Neural networks are able to approximate any continuous function on a compact set. However, it is not obvious how to quantify the error of the neural network, i.e., the remaining bi…