Package index • colSBM

User functions

clusterize_networks(): Partition of a collection of networks based on their common mesoscale structures

estimate_colSBM(): Estimate a colSBM on a collection of networks

dist_bmpop_max(): Compute the dissimilarity between 2 mesoscale structures

extract_best_partition(): Extract the best partition from the list of model given by the functions clusterize_networks() or clusterize_bipartite_networks().

extract_clustering_dendrogram(): Convert to tree

adjust_colBiSBM(): Adjust a colBiSBM on a given point

clusterize_bipartite_networks(): Partition of a collection of bipartite networks based on their common mesoscale structures

dist_bisbmpop_max(): Compute the dissimilarity between 2 mesoscale structures for bipartite SBM

estimate_colBiSBM(): Estimate a colBiSBM on a collection of networks

generate_bipartite_collection(): Generate collection of bipartite networks

generate_unipartite_collection(): Generate collection of unipartite

colSBM R6 class objects

bmpop: An R6 Class object, a collection of model for population of sbm netowrks

fitSimpleSBMPop: An R6 Class object, a fitted population of netowrks sbm once $optimize() is done

bisbmpop: An R6 Class object, a collection of model for population of BiSBM networks

fitBipartiteSBMPop: The method to plot the fitBipartite objects

Generic methods

plot(<fitSimpleSBMPop>): Plot matrix summaries of the collection mesoscale structure

plot(<bmpop>): Plot the trace of the different criteria in function of the number of clusters

plot(<fitBipartiteSBMPop>): Plot matrix summaries of the collection mesoscale structure

plot(<bisbmpop>): Plot the state-space exploration plot for a bipartite collection object

Data

foodwebs: A collection of 8 food webs

dorebipartite: A collection of 15 plant-pollinator bipartite networks