A Python library for fitting and sampling vine copulas using PyTorch.
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Updated
Jul 20, 2026 - Python
A Python library for fitting and sampling vine copulas using PyTorch.
The MultiHazard R package provides tools for stationary multivariate statistical modeling such as of the joint distribution of MULTIple co-occurring HAZARDs.
GARCH vine copula study of dependence between 12 equity markets, with EGARCH marginals, R-vine copula, and Value at Risk backtesting in R.
Vine copula synthetic portfolio generation for insurance — exposure-aware, fidelity reporting
D-vine copula model for multi-year policyholder claim modelling
Copula models for insurance pricing — D-vine temporal dependence, two-part occurrence/severity
Modeling multivariate insurance risks using copula theory and Monte Carlo simulation.
Pure-PyTorch vine copula modelling — GPU-ready, differentiable, and fully API-compatible with pyvinecopulib.
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