Quasi-Random Sampling for Multivariate Distributions via Generative Neural Networks

DOI10.1080/10618600.2020.1868302OpenAlexW3119119768MaRDI QIDQ5066450

Avinash Prasad, Marius Hofert, Mu Zhu

Publication date: 29 March 2022

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

Full work available at URL: https://arxiv.org/abs/1811.00683

zbMATH Keywords

copulassums of dependent random variablesexpected shortfallmaximum mean discrepancyquasi-random numbersgenerative moment matching networks

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (4)

SELECTING BIVARIATE COPULA MODELS USING IMAGE RECOGNITION ⋮ Probabilistic forecast reconciliation: properties, evaluation and score optimisation ⋮ Discrepancy-based inference for intractable generative models using quasi-Monte Carlo ⋮ Dependence Model Assessment and Selection with DecoupleNets

Uses Software

• QRM
• TwoCop
• Adam
• CopulaModel
• Wasserstein GAN
• AdaGAN

Cites Work

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