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GitHub / majianthu / pycopent
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
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/majianthu%2Fpycopent
Stars: 134
Forks: 29
Open Issues: 0
License: gpl-3.0
Language: Python
Repo Size: 1.4 MB
Dependencies:
2
Created: about 4 years ago
Updated: 6 days ago
Last pushed: 6 days ago
Last synced: 6 days ago
Commit Stats
Commits: 75
Authors: 3
Mean commits per author: 25.0
Development Distribution Score: 0.493
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/majianthu/pycopent
Topics: causal-discovery, causality, change-detection, change-point-detection, changepoint, conditional-independence-test, conditional-mutual-information, copula, copula-entropy, correlation, entropy, granger-causality, hypothesis-testing, information-theory, mutual-information, normality-test, python, transfer-entropy, two-sample-test, variable-selection