alc {memnet} | R Documentation |
Computes the uncorrected or corrected average local clustering coffiecient.
alc(adj, types = "uncorrected", weights = NULL, mode = "undirected")
adj |
numeric matrix representing the adjacency matrix. |
types |
character. Either |
weights |
numeric vector of edge weights. Optional. |
mode |
character, either |
The uncorrected clustering coefficent is computed according to Watts &
Strogatz (1998). The corrected clustering coefficient normalizes the
uncorrected one by the average degree / n nodes
, i.e., the expected
average local clustering for an Erdös-Renyi random graph.
the corrected local clustering coefficient and/or the uncorrected clustering coefficient.
# get fluency data data(animal_fluency) # edge lists of fluency graphs edge_list = threshold_graph(animal_fluency) # get adjacency matrices adj = edg_to_adj(edge_list) # get local average clustering coefficient alc(adj) # get corrected local average clustering coefficient alc(adj, types = 'corrected')