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: 1.0.1
Depends: R (≥ 3.6.0)
Imports: e1071, ggplot2, ggthemes, gridExtra, nnet, Hmisc, reshape2, stringr, doParallel, caret, corrplot, foreach
Suggests: knitr, rmarkdown, testthat (≥ 2.1.0), data.table, covr
Published: 2021-02-22
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: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL (≥ 2)]
URL: https://github.com/TJetka/SLEMI
NeedsCompilation: no
Materials: README NEWS
CRAN checks: SLEMI results

Downloads:

Reference manual: SLEMI.pdf
Vignettes: SLEMI User Manual
Package source: SLEMI_1.0.1.tar.gz
Windows binaries: r-devel: SLEMI_1.0.1.zip, r-release: SLEMI_1.0.1.zip, r-oldrel: SLEMI_1.0.1.zip
macOS binaries: r-release: SLEMI_1.0.1.tgz, r-oldrel: SLEMI_1.0.tgz
Old sources: SLEMI archive

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