4 papers
Dimension Reduction in Multivariate Extremes via Latent Linear Factor Models
Alexis Boulin, Axel Bücher
We propose a new and interpretable class of high-dimensional tail dependence models based on latent linear factor structures. Specifically, extremal dependence of an observable vec…
Structured linear factor models for tail dependence
Alexis Boulin, Axel Bücher
A common object to describe the extremal dependence of a -variate random vector is the stable tail dependence function . Various parametric models have emerged, with a po…
Extrapolating into the Extremes with Minimum Distance Estimation
Alexis Boulin, Erik Haufs
Understanding complex dependencies and extrapolating beyond observations are key challenges in modeling environmental space-time extremes. To address this, we introduce a simplifyi…
Estimating Max-Stable Random Vectors with Discrete Spectral Measure using Model-Based Clustering
Alexis Boulin
This study introduces a novel estimation method for the entries and structure of a matrix in the linear factor model . This is applied to…