Estimation of Limiting Conditional Probabilities for Regularly Varying Time Series

Abstract

In this thesis we are concerned with estimation of clustering probabilities for univariate heavy tailed time series. We employ functional convergence of a bivariate tail empirical process to conclude asymptotic normality of an estimator of the clustering probabilities. Theoretical results are illustrated by simulation studies.