vistla: Detecting Influence Paths with Information Theory
Traces information spread through interactions between features, utilising information theory measures and a higher-order generalisation of the concept of widest paths in graphs.
In particular, 'vistla' can be used to better understand the results of high-throughput biomedical experiments, by organising the effects of the investigated intervention in a tree-like hierarchy from direct to indirect ones, following the plausible information relay circuits.
Due to its higher-order nature, 'vistla' can handle multi-modality and assign multiple roles to a single feature.
| Version: |
1.0.0 |
| Depends: |
R (≥ 3.5.0) |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2022-08-18 |
| Author: |
Miron B. Kursa 
[aut, cre] |
| Maintainer: |
Miron B. Kursa <m at mbq.me> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
yes |
| CRAN checks: |
vistla results |
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