1 citations · 1 across the 5 of their papers we have counts for
5 papers
Analysing Extreme Rainfall via a Geometric Framework
Ryan Campbell, Kristina Grolmusova, Lydia Kakampakou +1
Motivated by the EVA 2025 Data Challenge, we address the problem of predicting extreme rainfall in the eastern United States using data from a large ensemble of climate model runs.…
Geometric criteria for identifying extremal dependence and flexible modeling via additive mixtures
Jeongjin Lee, Jennifer Wadsworth
The framework of geometric extremes is based on the convergence of scaled sample clouds onto a limit set, characterized by a gauge function, with the shape of the limit set determi…
X-Vine Models for Multivariate Extremes
Anna Kiriliouk, Jeongjin Lee, Johan Segers
Regular vine sequences permit the organisation of variables in a random vector along a sequence of trees. Regular vine models have become greatly popular in dependence modelling as…
Hypothesis testing for partial tail correlation in multivariate extremes
Mihyun Kim, Jeongjin Lee
Statistical modeling of high dimensional extremes remains challenging and has generally been limited to moderate dimensions. Understanding structural relationships among variables…
Transformed Linear Prediction for Extremes
Jeongjin Lee, Daniel Cooley
We address the problem of prediction for extreme observations by proposing an extremal linear prediction method. We construct an inner product space of nonnegative random variables…