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
Depends: R (≥ 3.6.0)
Imports: e1071, ggplot2, ggthemes, gridExtra, nnet, Hmisc, reshape2, stringr, doParallel, caret, corrplot, foreach
Suggests: knitr, rmarkdown
Published: 2019-10-07
Author: Tomasz Jetka [aut, cre], Karol Nienaltowski [ctb], Michal Komorowski [ctb]
Maintainer: Tomasz Jetka <t.jetka at>
License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL (≥ 2)]
NeedsCompilation: no
CRAN checks: SLEMI results


Reference manual: SLEMI.pdf
Vignettes: SLEMI User Manual
Package source: SLEMI_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel: not available
OS X binaries: r-release: SLEMI_1.0.tgz, r-oldrel: not available


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