[ANN] VineCopulas.jl: C-vines, D-vines, and experimental R-vines in Julia

Package Announcements
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Hi everyone,

I’m happy to announce that VineCopulas.jl is now registered in the Julia General registry.

VineCopulas.jl is a pure-Julia package for explicit vine copula models, built on top of Copulas.jl. The current release focuses on constructing vine copulas from bivariate pair-copulas, evaluating densities, simulating observations, and working with Rosenblatt and inverse Rosenblatt transforms.

Package installation:

using Pkg
Pkg.add("VineCopulas")

Documentation:

Repository:

The current version includes:

  • stable CVineCopula and DVineCopula model types;
  • experimental RVineCopula support for explicit structures;
  • pdf, logpdf, rand, numerical cdf, and simulate_qmc;
  • Rosenblatt and inverse Rosenblatt transforms;
  • truncated C-vines and D-vines;
  • pair-copula conditional primitives: hfunc1, hfunc2, hinv1, and hinv2;
  • model summaries such as loglikelihood, npars, aic, and bic;
  • reproducible benchmark and validation scripts against rvinecopulib.

This is an early release, so feedback, bug reports, suggestions, and contributions are very welcome.

One important note: VineCopulas.jl is currently focused on explicit vine construction and simulation/transform workflows. It does not yet provide automatic structure selection, family selection, or parameter estimation. These are planned for future versions.

Thanks to the Julia copula ecosystem, especially Copulas.jl, which made it much easier to build this package in a modular way.

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