DESCRIPTION

Package: BiCausality
Title: Binary Causality Inference Framework
Version: 0.1.4
Authors@R: 
    person(given = "Chainarong",
           family = "Amornbunchornvej",
           role = c("aut", "cre"),
           email = "grandca@gmail.com",
           comment = c(ORCID = "0000-0003-3131-0370"))
Maintainer: Chainarong Amornbunchornvej <grandca@gmail.com>
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>.
License: MIT + file LICENSE
URL: https://github.com/DarkEyes/BiCausality
BugReports: https://github.com/DarkEyes/BiCausality/issues
Depends: 
    R (>= 3.5.0)
Encoding: UTF-8
LazyData: TRUE
Roxygen: list(markdown = TRUE)
Suggests: knitr, rmarkdown, markdown, igraph
VignetteBuilder: knitr 
RoxygenNote: 7.2.3