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BiCausality

Binary Causality Inference Framework

v0.1.4 · Nov 27, 2023 · MIT + file LICENSE

Description

A framework to infer causality on binary data using techniques in frequent pattern mining and estimation statistics. Given a set of individual vectors S={x} where x(i) is a realization value of binary variable i, the framework infers empirical causal relations of binary variables i,j from S in a form of causal graph G=(V,E) where V is a set of nodes representing binary variables and there is an edge from i to j in E if the variable i causes j. The framework determines dependency among variables as well as analyzing confounding factors before deciding whether i causes j. The publication of this package is at Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, and Suttipong Thajchayapong (2023) <doi:10.1016/j.heliyon.2023.e15947>.

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Version History

new 0.1.4 Mar 10, 2026
updated 0.1.4 ← 0.1.3 diff Nov 27, 2023
updated 0.1.3 ← 0.1.2 diff May 21, 2023
updated 0.1.2 ← 0.1.1 diff Aug 18, 2022
new 0.1.1 May 25, 2022