transfer-entropy

JIDT: Java Information Dynamics Toolkit for studying information-theoretic measures of computation in complex systems

The Information Dynamics Toolkit xl (IDTxl) is a comprehensive software package for efficient inference of networks and their node dynamics from multivariate time series data using information theory.

Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python

Algorithms for quantifying associations, independence testing and causal inference from data.

Python package for calculating various information measures, including entropy, mutual information, transfer entropy, and more, with support for both discrete and continuous variables.

A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.

Code for the paper "Estimating Transfer Entropy via Copula Entropy"

R package for estimating copula entropy (mutual information), transfer entropy (conditional mutual information), and the statistic for multivariate normality test and two-sample test

A cross platform C library for information analysis of dynamical systems

Python Implementation of Transfer Entropy Method

Pythonic implementation of the Phase Transfer Entropy method using NumPy and SciPy

Code for paper "A method for detecting causal relationships between industrial alarm variables using Transfer entropy and K2-Algorithm"

Python module for computing Symbolic Mutual Information and symbolic Transfer of Entropy

Transfer entropy (conditional mutual information) estimators for the Julia language

My implementation of Symbolic Transfer Entropy (STE): a measure of asymmetric information flow between stochastic processes.

Continuous-Time Event-based Transfer Entropy

Rust library for calculating various information-theoretic measures, including entropy, mutual information, transfer entropy, and more, with support for both discrete and continuous variables.

This repository contains the code for the paper titled "Cryptocurrencies in the Balance Sheet: Insights from (Micro)Strategy - Bitcoin Interactions"

Official Python implementation of the Pioneer Detection Method (PDM) — convergence-based expert aggregation and opinion pooling under structural change. Code for Vansteenberghe (2026), The Geneva Papers 51(1).