The tail process Y=(Y i) i∈ Z d of a stationary regularly varying random field X=(X i) i∈ Z d
represents the asymptotic local distribution of X as seen from its typical exceedance over a …

In the regularly varying time series setting, a cluster of exceedances is a short period for
which the supremum norm exceeds a high threshold. We propose to study a generalization …

Heavy rainfall distributional modeling is essential in any impact studies linked to the water
cycle, for example, flood risks. Still, statistical analyses that both take into account the …

Extremes occur in stationary regularly varying time series as short periods with several large
observations, known as extremal blocks. We study cluster statistics summarizing the …

For the understanding of the behavior of the extremes of a stationary time series, the
analysis of the extremal dependence in time is of high importance. For quantities describing …

Nowadays, it is common in environmental sciences to use extreme value theory to assess
the risk of natural hazards. In hydrology, rainfall amounts reach high-intensity levels …

First, we complement the case study of heavy rainfall in France by implementing Pareto-
based methods using declustering techniques. Second, we develop on the asymptotic …

In the regularly varying time series setting, a cluster of exceedances is a short period for
which the supremum norm exceeds a high threshold. We propose to study a generalization …

The framework of regularly varying time series allows us to describe the extremal
dependence structure of multivariate (heavy-tailed) time series by means of the spectral tail …