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Copula Python Packages

Python packages with the GitHub topic copula. Sorted by relevance, with stars and monthly downloads.
DanielBok
copulae

Multivariate data modelling with Copulas in Python

14K 161 28
AANovokhatskiy
pyscarcopula

Python library for modelling complex multivariate dependencies using stochastic copulas

5K 2 0
TY-Cheng
torchvinecopulib

A Python library for fitting and sampling vine copulas using PyTorch.

1K 249 24
maximenc
pycop

Copula for multivariate dependence modeling

845 118 23
majianthu
copent

Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python

781 168 31
Bluerrror
torchvine

Pure-PyTorch vine copula modelling — GPU-ready, differentiable, and API-compatible with pyvinecopulib

475 0 0
burning-cost
insurance-frequency-severity

Sarmanov copula joint frequency-severity for insurance pricing — analytical premium correction, IFM estimation, dependency diagnostics

376 0 0
burning-cost
insurance-synthetic

Vine copula synthetic portfolio generation for insurance — exposure-aware, fidelity reporting

323 0 0
asnelt
mixedvines

Python package for canonical vine copula trees with mixed continuous and discrete marginals

271 49 9
safouaneelg
copulasimilarity

Official implementation of the paper: "CSIM: A Copula-based similarity index sensitive to local changes for Image quality assessment"

191 11 0
dmey
synthia

📈 🐍 Multidimensional synthetic data generation with Copula and fPCA models in Python

146 68 10
burning-cost
insurance-dependent-fs

Dependent frequency-severity neural two-part model for insurance pricing — shared encoder trunk, Poisson/Gamma heads, MC and analytical pure premium

143 0 0
burning-cost
insurance-copula

Copula models for insurance pricing — D-vine temporal dependence, two-part occurrence/severity

89 0 0
NazBen
dep-impact

A Python package on the influence of dependencies in a structural reliability problem.

45 1 0
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