We are interested in creating statistical methods to provide informative...
Extreme precipitation events with large spatial extents may have more se...
We propose a novel extremal dependence measure called the partial
tail-c...
To accurately quantify landslide hazard in a region of Turkey, we develo...
This review paper surveys recent development in software implementations...
In this work, we develop a constructive modeling framework for extreme
t...
Accurate spatiotemporal modeling of conditions leading to moderate and l...
Classical models for multivariate or spatial extremes are mainly based u...
Max-infinitely divisible (max-id) processes play a central role in
extre...
The conditional extremes framework allows for event-based stochastic mod...
Statistical models for landslide hazard enable mapping of risk factors a...
The modeling of spatio-temporal trends in temperature extremes can help
...
We develop a method for probabilistic prediction of extreme value hot-sp...
In agricultural landscapes, the composition and spatial configuration of...
Due to climate change and human activity, wildfires are expected to beco...
Nonparametric resampling methods such as Direct Sampling are powerful to...
We develop new flexible univariate models for light-tailed and heavy-tai...
Landslides are nearly ubiquitous phenomena and pose severe threats to pe...
A bivariate random vector can exhibit either asymptotic independence or
...
The probability and structure of co-occurrences of extreme values in
mul...
This work has been motivated by the challenge of the 2017 conference on
...
Extreme-value theory for stochastic processes has motivated the statisti...