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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>.

Versions across snapshots

VersionRepositoryFileSize
1.0.2 rolling linux/jammy R-4.5 SLEMI_1.0.2.tar.gz 1.4 MiB
1.0.2 rolling linux/noble R-4.5 SLEMI_1.0.2.tar.gz 1.4 MiB
1.0.2 rolling source/ R- SLEMI_1.0.2.tar.gz 2.0 MiB
1.0.2 latest linux/jammy R-4.5 SLEMI_1.0.2.tar.gz 1.4 MiB
1.0.2 latest linux/noble R-4.5 SLEMI_1.0.2.tar.gz 1.4 MiB
1.0.2 latest source/ R- SLEMI_1.0.2.tar.gz 2.0 MiB
1.0.2 2026-04-26 source/ R- SLEMI_1.0.2.tar.gz 2.0 MiB
1.0.2 2026-04-23 source/ R- SLEMI_1.0.2.tar.gz 2.0 MiB
1.0.2 2026-04-09 windows/windows R-4.5 SLEMI_1.0.2.zip 1.4 MiB
1.0.2 2025-04-20 source/ R- SLEMI_1.0.2.tar.gz 2.0 MiB

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