Welcome to the UNITE Toolbox’s documentation!

The UNITE Toolbox is a Python library for incorporating Information Theory to any data analysis and/or modelling workflows. The toolbox collects different estimation methods for information-theoretic quantities, and brings them together in an easy to use Python package with a simple interface.

Current available methods:

• Histograms or “binning”

• Kernel based estimation (KDE)

• k-nearest neighbors estimation (k-NN)

Check out the Usage section for further information, including how to install the project.

Note

This project is under active development.

Contents:

• Usage
  • Installation
  • Estimation
• Estimators
  • Binning
  • KDE
  • k-NN
• Utilities
  • Bootstrapping
  • Data Validation
  • Marginal Scores
  • Sampling
• Tutorials
  • Tutorial: \(k\)-NN for Information Theory
  • Tutorial: Non-parametric Density Estimation

Indices and tables

• Index

• Search Page