The paper introduces a graphical conditional extreme value model with asymmetric Gaussian residuals that captures both asymptotic dependence and independence and supports stepwise inference in high dimensions.
This supports our claim that the stepwise inference procedures result in no loss of information
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Conditional Extremes with Graphical Models
The paper introduces a graphical conditional extreme value model with asymmetric Gaussian residuals that captures both asymptotic dependence and independence and supports stepwise inference in high dimensions.