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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.

Version: 0.8.0
Depends: R (≥ 3.1.2)
Imports: Rcpp, KernSmooth, poorman
LinkingTo: Rcpp
Suggests: testthat, knitr, rmarkdown, microbenchmark
Published: 2023-12-02
Author: Hajk-Georg Drost ORCID iD [aut, cre], Jakub Nowosad ORCID iD [ctb]
Maintainer: Hajk-Georg Drost <hajk-georg.drost at tuebingen.mpg.de>
BugReports: https://github.com/drostlab/philentropy/issues
License: GPL-2
URL: https://github.com/drostlab/philentropy
NeedsCompilation: yes
Citation: philentropy citation info
Materials: README NEWS
CRAN checks: philentropy results

Documentation:

Reference manual: philentropy.pdf
Vignettes: Distances
Information Theory
Introduction
Comparing many probability density functions

Downloads:

Package source: philentropy_0.8.0.tar.gz
Windows binaries: r-devel: philentropy_0.8.0.zip, r-release: philentropy_0.8.0.zip, r-oldrel: philentropy_0.8.0.zip
macOS binaries: r-release (arm64): philentropy_0.8.0.tgz, r-oldrel (arm64): philentropy_0.8.0.tgz, r-release (x86_64): philentropy_0.8.0.tgz, r-oldrel (x86_64): philentropy_0.8.0.tgz
Old sources: philentropy archive

Reverse dependencies:

Reverse imports: biomartr, codez, EcotoneFinder, EnvNJ, GRelevance, iSubGen, jenga, LDLcalc, motif, mSigTools, musicatk, naive, noisyr, regional, segen, SemNeT, spooky, supercells, tetragon
Reverse suggests: miaSim, mmb, Rfast

Linking:

Please use the canonical form https://CRAN.R-project.org/package=philentropy to link to this page.

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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