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 + fileLICENSE |
| 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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