Dependence Model Assessment and Selection with DecoupleNets

DOI10.1080/10618600.2022.2157835arXiv2202.03406OpenAlexW4311305973MaRDI QIDQ6181399

Marius Hofert, Avinash Prasad, Mu Zhu

Publication date: 22 January 2024

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2202.03406

zbMATH Keywords

neural networksmodel selectioncopulasmodel assessmentgraphical approachRosenblatt transformation

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Selecting and estimating regular vine copulae and application to financial returns
• Goodness-of-fit tests for copulas: A review and a power study
• Sliced and Radon Wasserstein barycenters of measures
• Quasi-Random Sampling for Multivariate Distributions via Generative Neural Networks
• Simulating from Exchangeable Archimedean Copulas
• Elements of Copula Modeling with R
• Remarks on a Multivariate Transformation

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