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.

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"

Python Implementation of Transfer Entropy Method

A cross platform C library for information analysis of dynamical systems

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

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

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

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"

Information-theoretic social neuroscience analyses, particularly for hyperscanning paradigms

This is a Reproduction of the paper on fault detection using Multiscale Partial Symbolic Transfer Entropy in MATLAB. 对于关于用Multiscale Partial Symbolic Transfer Entropy实现故障检测的论文的matlab复现