bioregion: Comparison of Bioregionalisation Methods

The main purpose of this package is to propose a transparent methodological framework to compare bioregionalisation methods based on hierarchical and non-hierarchical clustering algorithms (Kreft & Jetz (2010) <doi:10.1111/j.1365-2699.2010.02375.x>) and network algorithms (Lenormand et al. (2019) <doi:10.1002/ece3.4718> and Leroy et al. (2019) <doi:10.1111/jbi.13674>).

Version: 1.0.0
Depends: R (≥ 4.0.0)
Imports: ape, bipartite, cluster, data.table, dbscan, dynamicTreeCut, fastcluster, ggplot2, grDevices, igraph, mathjaxr, Matrix, Rdpack, rlang, rmarkdown, segmented, sf, stats, tidyr, utils
LinkingTo: Rcpp
Suggests: ade4, dplyr, knitr, microbenchmark, rnaturalearth, rnaturalearthdata, testthat (≥ 3.0.0)
Published: 2023-04-14
Author: Maxime Lenormand ORCID iD [aut, cre], Boris Leroy ORCID iD [aut], Pierre Denelle ORCID iD [aut]
Maintainer: Maxime Lenormand <maxime.lenormand at inrae.fr>
BugReports: https://github.com/bioRgeo/bioregion/issues
License: GPL-3
URL: https://github.com/bioRgeo/bioregion, https://bioRgeo.github.io/bioregion/
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: bioregion results

Documentation:

Reference manual: bioregion.pdf
Vignettes: 1. Installation of the binary files
2. Matrix and network formats
Tutorial for bioregion

Downloads:

Package source: bioregion_1.0.0.tar.gz
Windows binaries: r-devel: bioregion_1.0.0.zip, r-release: bioregion_1.0.0.zip, r-oldrel: bioregion_1.0.0.zip
macOS binaries: r-release (arm64): bioregion_1.0.0.tgz, r-oldrel (arm64): bioregion_1.0.0.tgz, r-release (x86_64): bioregion_1.0.0.tgz

Linking:

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