4 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.…
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…
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…
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…