Package: philentropy 0.10.0
philentropy: Similarity and Distance Quantification Between Probability Functions
Computes 46 optimized distance and similarity measures for comparing probability functions (Drost (2018) <doi:10.21105/joss.00765>). These comparisons between probability functions have their foundations in a broad range of scientific disciplines from mathematics to ecology. The aim of this package is to provide a core framework for clustering, classification, statistical inference, goodness-of-fit, non-parametric statistics, information theory, and machine learning tasks that are based on comparing univariate or multivariate probability functions.
Authors:
philentropy_0.10.0.tar.gz
philentropy_0.10.0.zip(r-4.7)philentropy_0.10.0.zip(r-4.6)philentropy_0.10.0.zip(r-4.5)
philentropy_0.10.0.tgz(r-4.6-x86_64)philentropy_0.10.0.tgz(r-4.6-arm64)philentropy_0.10.0.tgz(r-4.5-x86_64)philentropy_0.10.0.tgz(r-4.5-arm64)
philentropy_0.10.0.tar.gz(r-4.7-arm64)philentropy_0.10.0.tar.gz(r-4.7-x86_64)philentropy_0.10.0.tar.gz(r-4.6-arm64)philentropy_0.10.0.tar.gz(r-4.6-x86_64)
philentropy_0.10.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
philentropy/json (API)
NEWS
| # Install 'philentropy' in R: |
| install.packages('philentropy', repos = c('https://drostlab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/drostlab/philentropy/issues
Pkgdown/docs site:https://drostlab.github.io
distance-measuresdistance-quantificationinformation-theoryjensen-shannon-divergenceparametric-distributionssimilarity-measuresstatisticscpp
Last updated from:9e171b253f. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 187 | ||
| linux-devel-x86_64 | OK | 143 | ||
| source / vignettes | OK | 187 | ||
| linux-release-arm64 | OK | 178 | ||
| linux-release-x86_64 | OK | 120 | ||
| macos-release-arm64 | OK | 95 | ||
| macos-release-x86_64 | OK | 247 | ||
| macos-oldrel-arm64 | OK | 96 | ||
| macos-oldrel-x86_64 | OK | 178 | ||
| windows-devel | OK | 137 | ||
| windows-release | OK | 175 | ||
| windows-oldrel | OK | 122 | ||
| wasm-release | OK | 104 |
Exports:additive_symm_chi_sqavgbhattacharyyabinned.kernel.estcanberraCEchebyshevclark_sqcosine_distczekanowskidice_distdist_many_manydist_one_manydist_one_onedist.diversitydistancedivergence_sqestimate.probabilityeuclideanfidelitygetDistMethodsgJSDgowerHharmonic_mean_disthellingerinner_productintersection_distjaccardJEjeffreysjensen_differencejensen_shannonJSDk_divergenceKLkulczynski_dkullback_leibler_distancekumar_hassebrookkumar_johnsonlin.corlorentzianmanhattanmatusitaMIminkowskimotykaneyman_chi_sqpearson_chi_sqprob_symm_chi_sqruzickasoergelsorensensquared_chi_sqsquared_chordsquared_euclideantanejatanimototopsoewave_hedges
Dependencies:KernSmoothpoormanRcppRcppParallel
Comparing many probability density functions
Rendered fromMany_Distances.Rmdusingknitr::rmarkdownon May 13 2026.Last update: 2025-10-31
Started: 2021-08-20
Distances
Rendered fromDistances.Rmdusingknitr::rmarkdownon May 13 2026.Last update: 2022-11-06
Started: 2015-03-26
Information Theory
Rendered fromInformation_Theory.Rmdusingknitr::rmarkdownon May 13 2026.Last update: 2022-11-06
Started: 2015-04-28
Introduction
Rendered fromIntroduction.Rmdusingknitr::rmarkdownon May 13 2026.Last update: 2025-11-03
Started: 2015-03-26
