setweaver: Building Sets of Variables in a Probabilistic Framework
Create sets of variables based on a mutual
information approach. In this context, a set is a collection of
distinct elements (e.g., variables) that can also be treated as a
single entity. Mutual information, a concept from probability theory,
quantifies the dependence between two variables by expressing how much
information about one variable can be gained from observing the other.
Furthermore, you can analyze, and visualize
these sets in order to better understand the relationships among
variables.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
dplyr (≥ 1.1.4), igraph (≥ 2.1.2), permutes (≥ 2.8), pheatmap (≥ 1.0.13), splitTools (≥ 1.0.1) |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2026-02-04 |
| DOI: |
10.32614/CRAN.package.setweaver (may not be active yet) |
| Author: |
Nicolas Leenaerts 
[aut, cre, cph],
Aaron Fisher
[aut, cph] |
| Maintainer: |
Nicolas Leenaerts <nicolas.leenaerts at kuleuven.be> |
| License: |
CC BY 4.0 |
| URL: |
https://github.com/nicolasleenaerts/setweaver |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
setweaver results |
Documentation:
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