R: Comparison of Bioregionalization Methods

# Comparison of Bioregionalization Methods

## Documentation for package ‘bioregion’ version 1.4.0

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

as_bioregion_pairwise | Convert a matrix or list of matrices to a bioregion (dis)similarity object
betapart_to_bioregion | Convert betapart dissimilarity to bioregion dissimilarity (DEPRECATED)
bind_pairwise | Combine and enrich bioregion (dis)similarity object(s)
bioregionalization_metrics | Calculate metrics for one or several bioregionalizations
bioregion_colors | Add color palettes to bioregion cluster objects
bioregion_metrics | Calculate metrics for bioregions
compare_bioregionalizations | Compare cluster memberships among multiple bioregionalizations
cut_tree | Cut a hierarchical tree
dissimilarity | Compute dissimilarity metrics (beta-diversity) between sites based on species composition
dissimilarity_to_similarity | Convert dissimilarity metrics to similarity metrics
exportGDF | Export a network to GDF format for Gephi visualization
find_optimal_n | Search for an optimal number of clusters in a list of bioregionalizations
fishdf | Spatial distribution of fish in Europe (data.frame)
fishmat | Spatial distribution of fish in Europe (co-occurrence matrix)
fishsf | Spatial distribution of fish in Europe
hclu_diana | Divisive hierarchical clustering based on dissimilarity or beta-diversity
hclu_hierarclust | Hierarchical clustering based on dissimilarity or beta-diversity
hclu_optics | OPTICS hierarchical clustering algorithm
install_binaries | Download, unzip, check permissions, and test the bioregion's binary files
map_bioregions | Create a map of bioregions
mat_to_net | Create a data.frame from a contingency table
netclu_beckett | Community structure detection in weighted bipartite networks via modularity optimization
netclu_greedy | Community structure detection via greedy optimization of modularity
netclu_infomap | Infomap community finding
netclu_labelprop | Finding communities based on propagating labels
netclu_leadingeigen | Finding communities based on the leading eigenvector of the community matrix
netclu_leiden | Finding communities using the Leiden algorithm
netclu_louvain | Louvain community finding
netclu_oslom | OSLOM community finding
netclu_walktrap | Community structure detection via short random walks
net_to_mat | Create a contingency table from a data.frame
nhclu_affprop | Non-hierarchical clustering: Affinity Propagation
nhclu_clara | Non-hierarchical clustering: CLARA
nhclu_clarans | Non-hierarchical clustering: CLARANS
nhclu_dbscan | Non-hierarchical clustering: DBSCAN
nhclu_kmeans | Non-hierarchical clustering: K-means analysis
nhclu_pam | Non-hierarchical clustering: Partitioning Around Medoids
similarity | Compute similarity metrics between sites based on species composition
similarity_to_dissimilarity | Convert similarity metrics to dissimilarity metrics
site_species_metrics | Calculate metrics for sites and species relative to bioregions and chorotypes
site_species_subset | Extract a subset of sites or species from a 'bioregion.clusters' object
vegedf | Spatial distribution of Mediterranean vegetation (data.frame)
vegemat | Spatial distribution of Mediterranean vegetation (co-occurrence matrix)
vegesf | Spatial distribution of Mediterranean vegetation (sf data.frame)