Supplement to “Extremes on river networks”. The supplementary material contains the
following: a PDF document containing the derivation of the new likelihood representation …

Max-stable processes play an important role as models for spatial extreme events. Their
complex structure as the pointwise maximum over an infinite number of random functions …

Estimation of extreme value parameters from observations in the max-domain of attraction of
a multivariate max-stable distribution commonly uses aggregated data such as block …

The health consequences of climate variability and change are diverse, potentially affecting
the burden of a wide range of health outcomes, including illnesses and deaths related to …

Recent advances in extreme value theory have established-Pareto processes as the natural
limits for extreme events defined in terms of exceedances of a risk functional. In this paper …

Max-stable processes have proved to be useful for the statistical modelling of spatial
extremes. Several families of max-stable random fields have been proposed in the literature …

To improve the forecasts of weather extremes, we propose a joint spatial model for the
observations and the forecasts, based on a bivariate Brown-Resnick process. As the class of …

We study the dynamics of the outliers for a large number of independent Brownian particles
in one dimension. We derive the multitime joint distribution of the position of the rightmost …

Max-stable processes allow the spatial dependence of extremes to be modelled and
quantified, so they are widely adopted in applications. For a better understanding of …

The distribution of spatially aggregated data from a stochastic process may exhibit tail
behaviour different from that of its marginal distributions. For a large class of aggregating …