Conditional KDE

Conditional Kernel Density Estimation

A Python package for conditional kernel density estimation. This library provides efficient implementations for estimating conditional probability densities using kernel methods.

• Free software: MIT license
• Documentation: https://conditional-kde.readthedocs.io
• PyPI: https://pypi.org/project/conditional_kde/
• Source Code: https://github.com/dprelogo/conditional_kde

Installation

Install from PyPI:

pip install conditional_kde

For development installation:

git clone https://github.com/dprelogo/conditional_kde.git
cd conditional_kde
pip install -e .[dev]

Quick Start

from conditional_kde import ConditionalKDE

# Example usage
ckde = ConditionalKDE()
# Add your code example here

Features

• Gaussian and interpolated kernel density estimation
• Support for conditional density estimation
• Efficient implementation using NumPy and SciPy
• Comprehensive test coverage
• Type hints for better IDE support

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.