Clustering of exceedances of a critical level is a phenomenon that concerns risk managers
in many areas. The extremal index θ measures the propensity of the large observations in a …

The extremal index is an important parameter in the characterization of extreme values of a
stationary sequence. Our new estimation approach for this parameter is based on the …

As part of global climate change an accelerated hydrologic cycle (including an increase in
heavy precipitation) is anticipated. So, it is of great importance to be able to quantify high …

Abstract top In what concerns extreme values modeling, heavy tailed autoregressive
processes defined with the minimum or maximum operator have proved to be good …

This article concerns the estimation of hitting time statistics for potentially non-stationary
processes. The main focus is exceedance times of environmental processes. To this end we …

The occurrence of successive extreme observations can have an impact on society. In
extreme value theory there are parameters to evaluate the effect of clustering of high values …

Financial crises are a recurrent phenomenon with important effects on the real economy.
The financial system is inherently fragile and it is therefore of great importance to be able to …

The well-known M4 processes of Smith and Weissman are very flexible models for
asymptotically dependent multivariate data. Extended M4 of Heffernan et al. allows to also …

For stationary sequences, under general dependence restrictions, any limiting point process
for time normalized upcrossings of high levels is a compound Poisson process, ie, there is a …

The extremal index θ is an important parameter in extreme value analysis when extending
results from independent and identically distributed sequences to stationary ones. A …