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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.
Version: | 0.9.0 |
Depends: | R (≥ 3.1.2) |
Imports: | Rcpp, KernSmooth, poorman |
LinkingTo: | Rcpp |
Suggests: | testthat, knitr, rmarkdown, microbenchmark |
Published: | 2024-11-12 |
DOI: | 10.32614/CRAN.package.philentropy |
Author: | Hajk-Georg Drost [aut, cre], Jakub Nowosad [ctb] |
Maintainer: | Hajk-Georg Drost <hajk-georg.drost at tuebingen.mpg.de> |
BugReports: | https://github.com/drostlab/philentropy/issues |
License: | GPL-2 |
URL: | https://drostlab.github.io/philentropy/, https://github.com/drostlab/philentropy |
NeedsCompilation: | yes |
Citation: | philentropy citation info |
Materials: | README NEWS |
CRAN checks: | philentropy results |
Reference manual: | philentropy.pdf |
Vignettes: |
Distances (source) Information Theory (source) Introduction (source) Comparing many probability density functions (source, R code) |
Package source: | philentropy_0.9.0.tar.gz |
Windows binaries: | r-devel: philentropy_0.9.0.zip, r-release: philentropy_0.9.0.zip, r-oldrel: philentropy_0.9.0.zip |
macOS binaries: | r-release (arm64): philentropy_0.9.0.tgz, r-oldrel (arm64): philentropy_0.9.0.tgz, r-release (x86_64): philentropy_0.9.0.tgz, r-oldrel (x86_64): philentropy_0.9.0.tgz |
Old sources: | philentropy archive |
Reverse imports: | biomartr, codez, EcotoneFinder, EnvNJ, GRelevance, iSubGen, jenga, motif, mSigTools, musicatk, naive, noisyr, regional, segen, SemNeT, spooky, supercells, tetragon |
Reverse suggests: | miaSim, mmb, priorsense, Rfast, tidytof |
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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.
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