5 papers
Calibrating simplified vine copulas with a noise contrastive estimation approach
Michael Denis Kraus, David Huk, Claudia Czado
Vine copulas provide a flexible framework for modeling complex multivariate dependence structures using only bivariate building blocks. Their practical success relies heavily on th…
Stepwise Variational Inference with Vine Copulas
Elisabeth Griesbauer, Leiv Rønneberg, Arnoldo Frigessi +2
We propose stepwise variational inference (VI) with vine copulas: a universal VI procedure that combines vine copulas with a novel stepwise estimation procedure of the variational…
Bivariate Postprocessing of Wind Vectors
Ferdinand Buchner, David Jobst, Annette Möller +1
To quantify the uncertainty in numerical weather prediction (NWP) forecasts, ensemble prediction systems are utilized. Although NWP forecasts continuously improve, they suffer from…
Sampling from Conditional Distributions of Simplified Vines
Ariane Hanebeck, Ãzge Åahin, Petra HavlÃÄková +1
Simplified vine copulas are flexible tools over standard multivariate distributions for modeling and understanding different dependence properties in high-dimensional data. Their c…
TVineSynth: A Truncated C-Vine Copula Generator of Synthetic Tabular Data to Balance Privacy and Utility
Elisabeth Griesbauer, Claudia Czado, Arnoldo Frigessi +1
We propose TVineSynth, a vine copula based synthetic tabular data generator, which is designed to balance privacy and utility, using the vine tree structure and its truncation to d…