Metadata-Version: 1.1
Name: InfoPaths
Version: 0.1
Summary: Straight-forward causality analysis for continuous-valued data. We use the Kraskov-Stoegbauer-Grassberger (KSG) mutual information estimator for transfer entropy and conditional transfer entropy estimation, and the technique proposed by Duan et al. to distinguish direct and spurious causality.
Home-page: https://github.com/benjamin-ahlbrecht/InfoPaths
Author: Benjamin Ahlbrecht
Author-email: BenjaminAhlbrecht@gmail.com
License: MIT
Download-URL: https://github.com/benjamin-ahlbrecht/InfoPaths/archive/refs/tags/v0.1-alpha.tar.gz
Description: UNKNOWN
Keywords: Information Theory,Transfer Entropy,Mutual Information,Statistical Inference,Conditional Transfer Entropy,Conditional Mutual Information,Nearest Neighbors,Direct Causality,Kraskov, Stoegbauer, Grassberger,Network Analysis,Time Series Analysis,Granger Causality
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.0
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
