SLEMI: Statistical Learning Based Estimation of Mutual Information
The implementation of the algorithm for estimation of mutual information and channel capacity from experimental data by classification procedures (logistic regression). Technically, it allows to estimate information-theoretic measures between finite-state input and multivariate, continuous output. Method described in Jetka et al. (2019) <doi:10.1371/journal.pcbi.1007132>.
| Version: |
1.0.2 |
| Depends: |
R (≥ 3.6.0) |
| Imports: |
e1071, ggplot2, gridExtra, nnet, Hmisc, reshape2, stringr, doParallel, caret, corrplot, foreach, methods |
| Suggests: |
knitr, rmarkdown, testthat (≥ 2.1.0), data.table, covr |
| Published: |
2023-11-19 |
| DOI: |
10.32614/CRAN.package.SLEMI |
| Author: |
Tomasz Jetka [aut, cre],
Karol Nienaltowski [ctb],
Michal Komorowski [ctb] |
| Maintainer: |
Tomasz Jetka <t.jetka at gmail.com> |
| BugReports: |
https://github.com/TJetka/SLEMI/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/TJetka/SLEMI |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
SLEMI results |
Documentation:
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