Copulas is a Python library for modeling multivariate distributions and sampling from them using copula functions. Given a table of numerical data, use Copulas to learn the distribution and generate new synthetic data following the same statistical properties. Choose from a variety of univariate distributions and copulas – including Archimedian Copulas, Gaussian Copulas and Vine Copulas. Compare real and synthetic data visually after building your model. Visualizations are available as 1D histograms, 2D scatterplots and 3D scatterplots. Access & manipulate learned parameters. With complete access to the internals of the model, set or tune parameters to your choosing.
Features
- Model multivariate data
- Compare real and synthetic data visually
- Access & manipulate learned parameters
- Visualize the real and synthetic data side-by-side
- Model the data using a copula and use it to create synthetic data
- The Copulas library offers many options including Gaussian Copula, Vine Copulas and Archimedian Copulas
Project Samples
Categories
Synthetic Data GenerationLicense
MIT LicenseFollow Copulas
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