Deep Extreme Value Copulas for Estimation and Sampling

• URL: http://arxiv.org/abs/2102.09042v1
• Date: Wed, 17 Feb 2021 22:02:47 GMT
• Title: Deep Extreme Value Copulas for Estimation and Sampling
• Authors: Ali Hasan, Khalil Elkhalil, Joao M. Pereira, Sina Farsiu, Jose H. Blanchet, Vahid Tarokh
• Abstract summary: We propose a new method for modeling the distribution function of high dimensional extreme value distributions. We present new methods for recovering the spectral representation of extreme distributions and propose a generative model for sampling from extreme copulas.
• Score: 35.93835819721815
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a new method for modeling the distribution function of high dimensional extreme value distributions. The Pickands dependence function models the relationship between the covariates in the tails, and we learn this function using a neural network that is designed to satisfy its required properties. Moreover, we present new methods for recovering the spectral representation of extreme distributions and propose a generative model for sampling from extreme copulas. Numerical examples are provided demonstrating the efficacy and promise of our proposed methods.

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