| Name | copul JSON |
| Version |
0.1.1
JSON |
| download |
| home_page | https://github.com/Corrram/copul |
| Summary | Mathematical computation and visualization of bivariate copulas. |
| upload_time | 2024-09-20 15:40:34 |
| maintainer | None |
| docs_url | None |
| author | Marcus Rockel |
| requires_python | <4.0,>=3.10 |
| license | None |
| keywords |
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| VCS |
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| bugtrack_url |
|
| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# copul
**copul** is a package designed for mathematical computation with and visualization of bivariate copula families.
# Install
Install the copul library using pip.
```bash
pip install copul
```
# Documentation
A guide and documentation is available at [https://copul.readthedocs.io/](https://copul.readthedocs.io/).
# Copula families and copulas
The `copul` package covers implementations of the following copula families:
- **Archimedean copula families**: The 22 Archimedean copula families from the book "Nelsen - An Introduction to Copulas" including
* Clayton
* Gumbel-Hougaard
* Frank
* Joe
* Ali-Mikhail-Haq
* etc.
- **Extreme-value copulas families**:
* BB5
* Cuadras-Augé
* Galambos
* Gumbel
* Husler-Reiss
* Joe
* Marshall-Olkin
* tEV
* Tawn
- **Elliptical copula families**:
* Gaussian
* Student's t
* Laplace.
- **Other copula families**:
* Farlie-Gumbel-Morgenstern
* Fréchet
* Mardia
* Plackett
* Raftery
Furthermore, the package provides the following copulas:
- Independence copula
- Lower and upper Fréchet bounds
- Checkerboard copulas
<!--A list of all implemented copulas can be found in `copul.Families`.
> **Note**: The following examples are also available as a Jupyter notebook in the `notes/examples` folder.-->
# Copula properties
The following properties are available for the above copula families and copulas if they exist and are known:
- `cdf`: Cumulative distribution function
- `pdf`: Probability density function
- `cond_distr_1`, `cond_distr_2`: Conditional distribution functions
- `lambda_L`, `lambda_U`: Lower and upper tail dependence coefficients
- `rho`, `tau`, `xi`: Spearman's rho, Kendall's tau, and Chatterjee's xi
- `generator`, `inv_generator`: Generator and inverse generator for Archimedean copula families
- `pickands`: Pickands dependence functions for extreme-value copula families
# Copula methods
The following methods are available for the above copula families and copulas:
- `rvs`: Generate random samples from the copula
- `scatter_plot`: Generate a scatter plot of the copula
- `plot_cdf`: Visualize the cumulative distribution function
- `plot_pdf`: Visualize the probability density function
- `plot_rank_correlations`: Visualize Spearman's rho, Kendall's tau, and Chatterjee's xi
- `plot_generator`: Visualize the generator function
- `plot_pickands`: Visualize the Pickands dependence function
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