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: 1.2.0 Depends: R (≥ 4.0.0) Imports: ape, apcluster, bipartite, cluster, data.table, dbscan, dynamicTreeCut, fastcluster, fastkmedoids, ggplot2, grDevices, httr, igraph, mathjaxr, Matrix, phangorn, Rdpack, rlang, rmarkdown, segmented, sf, stats, tidyr, utils LinkingTo: Rcpp Suggests: ade4, dplyr, knitr, microbenchmark, rnaturalearth, rnaturalearthdata, testthat (≥ 3.0.0) Published: 2025-01-31 DOI: 10.32614/CRAN.package.bioregion Author: Maxime Lenormand [aut, cre], Boris Leroy [aut], Pierre Denelle [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 resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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