kldest: Sample-Based Estimation of Kullback-Leibler Divergence
Estimation algorithms for Kullback-Leibler divergence between two probability distributions, based on one or two samples, and including uncertainty quantification. Distributions can be uni- or multivariate and continuous, discrete or mixed.
| Version: | 1.0.0 |
| Imports: | stats, RANN |
| Suggests: | knitr, rmarkdown, KernSmooth, testthat (≥ 3.0.0) |
| Published: | 2024-04-09 |
| DOI: | 10.32614/CRAN.package.kldest |
| Author: | Niklas Hartung 
[aut, cre, cph] |
| Maintainer: | Niklas Hartung <niklas.hartung at gmail.com> |
| BugReports: | https://github.com/niklhart/kldest/issues |
| License: | MIT + file LICENSE |
| URL: | https://niklhart.github.io/kldest/ |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | kldest results |
Documentation:
| Reference manual: | kldest.html , kldest.pdf |
Downloads:
| Package source: | kldest_1.0.0.tar.gz |
| Windows binaries: | r-devel: kldest_1.0.0.zip, r-release: kldest_1.0.0.zip, r-oldrel: kldest_1.0.0.zip |
| macOS binaries: | r-release (arm64): kldest_1.0.0.tgz, r-oldrel (arm64): kldest_1.0.0.tgz, r-release (x86_64): kldest_1.0.0.tgz, r-oldrel (x86_64): kldest_1.0.0.tgz |
Linking:
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