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 detecting associations, dynamical influences and causal inference from data.

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

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

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

Python Implementation of Transfer Entropy Method

A cross platform C library for information analysis of dynamical systems

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

A suite of MATLAB/C and C++ tools for computing standard and extended versions of Thomas Schreiber's transfer entropy on sparse, binary time series.

Code for the paper "Identifying time lag in dynamical systems with copula entropy based transfer entropy"

Calculation of Renye Transfer Entropy

Final group project of "Information Theory and Inference" course at University of Padova