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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 ORCID iD [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.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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.