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>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: SLEMI results


Reference manual: SLEMI.pdf
Vignettes: SLEMI User Manual


Package source: SLEMI_1.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SLEMI_1.0.2.tgz, r-oldrel (arm64): SLEMI_1.0.2.tgz, r-release (x86_64): SLEMI_1.0.2.tgz, r-oldrel (x86_64): SLEMI_1.0.2.tgz
Old sources: SLEMI archive


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