IDTxl
IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks. 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. IDTxl provides functionality to estimate the following measures: 1) For network inference: multivariate transfer entropy (TE)/Granger causality (GC), multivariate mutual information (MI), bivariate TE/GC, bivariate MI; 2) For analysis of node dynamics: active information storage (AIS), partial information decomposition (PID); IDTxl implements estimators for discrete and continuous data with parallel computing engines for both GPU and CPU platforms. Written for Python3.4.3+.
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References in zbMATH (referenced in 4 articles , 1 standard article )
Showing results 1 to 4 of 4.
Sorted by year (- Petri Laarne, Martha A. Zaidan, Tuomo Nieminen: ennemi: Non-linear correlation detection with mutual information (2021) not zbMATH
- Madhavun Candadai; Eduardo J. Izquierdo: infotheory: A C++/Python package for multivariate information theoretic analysis (2019) arXiv
- SimonBehrendt; ThomasDimpfl; Franziska J.Peter; David J.Zimmermann: RTransferEntropy - Quantifying information flow between different time series using effective transfer entropy (2019) not zbMATH
- Wollstadt; Patricia; Lizier; Joseph T.; Vicente; Raul; Finn; Conor; Martínez-Zarzuela; Mario; Mediano; Pedro; Novelli; Leonardo; Wibral; Michael: IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks (2018) arXiv