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This R package gathers a comprehensive set of algorithms to perform bioregionalisation analyses.
Bioregionalisation methods can be based on hierarchical clustering algorithms, non-hierarchical clustering algorithms or network algorithms.
The package can be installed with the following command line in R session:
From the CRAN
or from GitHub
We wrote several vignettes that will help you using the bioregion R package. Vignettes available are the following ones:
Alternatively, if you prefer to view the vignettes in R, you can install the package with build_vignettes = TRUE. But be aware that some vignettes can be slow to generate.
remotes::install_github("bioRgeo/bioregion",
dependencies = TRUE, upgrade = "ask",
build_vignettes = TRUE)
vignette("bioregion")An overview of all functions and data is given here.
Thank you for finding it. Head over to the GitHub Issues tab and let us know about it. Alternatively, you can also send us an e-mail. We will try to get to it as soon as we can!
bioregion depends on ape, bipartite, cluster, data.table, dbscan, dynamicTreeCut, earth, fastcluster, ggplot2, grDevices, igraph, mathjaxr, Matrix, Rcpp, Rdpack, rlang, rmarkdown, segmented,sf, stats, tidyr and utils.
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.
Health stats visible at Monitor.