• Corpus ID: 228375991

Structure learning for extremal tree models

@article{Engelke2020StructureLF,
  title={Structure learning for extremal tree models},
  author={Sebastian Engelke and Stanislav Volgushev},
  journal={arXiv: Methodology},
  year={2020}
}
Extremal graphical models are sparse statistical models for multivariate extreme events. The underlying graph encodes conditional independencies and enables a visual interpretation of the complex extremal dependence structure. For the important case of tree models, we develop a data-driven methodology for learning the graphical structure. We show that sample versions of the extremal correlation and a new summary statistic, which we call the extremal variogram, can be used as weights for a… 
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