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: |
1.1.1-1 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
ape, bipartite, cluster, data.table, dbscan, dynamicTreeCut, fastcluster, fastkmedoids, 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: |
2024-11-11 |
| 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 results |