stable | R Documentation |
Computes the within-community centrality for each node in the network
stable( A, comm = c("walktrap", "louvain"), cent = c("betweenness", "rspbc", "closeness", "strength", "degree", "hybrid"), absolute = TRUE, diagonal = 0, ... )
A |
An adjacency matrix of network data |
comm |
Can be a vector of community assignments or community detection algorithms
( |
cent |
Centrality measure to be used.
Defaults to |
absolute |
Should network use absolute weights?
Defaults to |
diagonal |
Sets the diagonal values of the |
... |
Additional arguments for |
A matrix containing the within-community centrality value for each node
Alexander Christensen <alexpaulchristensen@gmail.com>
Blanken, T. F., Deserno, M. K., Dalege, J., Borsboom, D., Blanken, P., Kerkhof, G. A., & Cramer, A. O. (2018). The role of stabilizing and communicating symptoms given overlapping communities in psychopathology networks. Scientific Reports, 8, 5854.
# Pearson's correlation only for CRAN checks A <- TMFG(neoOpen, normal = FALSE)$A stabilizing <- stable(A, comm = "walktrap")
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