With the advancement of spatial analysis approaches, methodological research addressing
the technical and statistical issues related to joint spatial and spatiotemporal models has …

A simultaneous autoregressive score-driven model with autoregressive disturbances is
developed for spatio-temporal data that may exhibit heavy tails. The model specification …

Widespread extreme climate events cause many fatalities, economic losses and have a
huge impact on critical infrastructure. It is therefore of utmost importance to estimate the …

The following sections are a start on organizing references on stable distributions by topic. It
is far from complete. Starting on page 23 there is an extensive list of papers, most on stable …

Given the common problem of missing data in real-world applications from various fields,
such as remote sensing, ecology and meteorology, the interpolation of missing spatial and …

We propose a novel extremal dependence measure called the partial tail-correlation
coefficient (PTCC), in analogy to the partial correlation coefficient in classical multivariate …

We present a method for the analysis and compact description of large-scale multivariate
weather extremes. Spatial patterns of extreme events are identified using the tail pairwise …

We provide the first statistical analysis of the dependence between maximum rainfall and
maximum temperature in Senegal. The data are from twelve stations spread across …

The block maxima approach is an important method in univariate extreme value analysis.
While assuming that block maxima are independent results in straightforward analysis, the …

We present the methods employed by team 'Uniofbathtopia'as part of a competition
organised for the 13th International Conference on Extreme Value Analysis (EVA2023) …