Copulas
Overview
Installing Copulas
Requirements
Install with pip
Install with conda
Install from source
Install for development
Quickstart
1. Load the data
2. Create a Copula instance
3. Fit the model
4. Sample new data
5. Load and save a model
6. Extract and set parameters
User Guides
Introduction to Copulas
Probability Review
Probability Density Function
Cumulative Distribution Function
Probability Integral Transform
Copulas
Univariate Distributions
Univariate Usage Example
Fitting the model
Sampling new data
Probability Density
Cumulative Distribution
to_dict and from_dict
Selecting the best Univariate
Fitting a generic Univariate
Recreating the Univariate
Univariate Families
Multivariate Distributions
Gaussian Multivariate
Fitting a Model and Generating Synthetic Data
Specifying column distributions
Probability Density and Cumulative Distribution
to_dict and from_dict
Vine Copulas
Advanced Usage
Synthetic Data for Machine Learning
Loading the dataset
Generating synthetic data
Training a linear model
Resources
API Reference
copulas.bivariate package
copulas.bivariate.base module
copulas.bivariate.clayton module
copulas.bivariate.frank module
copulas.bivariate.gumbel module
copulas.bivariate.independence module
copulas.bivariate.utils module
copulas.multivariate package
copulas.multivariate.base module
copulas.multivariate.gaussian module
copulas.multivariate.tree module
copulas.multivariate.vine module
copulas.optimize package
copulas.univariate package
copulas.univariate.base module
copulas.univariate.beta module
copulas.univariate.gamma module
copulas.univariate.gaussian module
copulas.univariate.gaussian_kde module
copulas.univariate.log_laplace module
copulas.univariate.selection module
copulas.univariate.student_t module
copulas.univariate.truncated_gaussian module
copulas.univariate.uniform module
copulas.datasets module
copulas.visualization module
Contributing
History
Copulas
Docs
»
Search
Edit on GitHub
Please activate JavaScript to enable the search functionality.