Description Usage Arguments Value Author(s) References Examples
Computes the mean distance across a subset of nodes in a network. This measure can be used to identify the effectiveness of a subset of nodes' coverage of the network space
1 | network.coverage(A, nodes, weighted = FALSE)
|
A |
An adjacency matrix |
nodes |
Subset of nodes to examine the coverage of the network |
weighted |
Is the network weighted?
Defaults to |
Returns a list containing:
mean |
The average distance from the subset of nodes to all other nodes in the network |
sd |
The standard deviation of distance from the subset of nodes to all other nodes in the network |
range |
The range of distance from the subset of nodes to all other nodes in the network |
Alexander Christensen <alexpaulchristensen@gmail.com> and Mathias Benedek <mathias.benedek@uni-graz.at>
Christensen, A. P., Cotter, K. N., Silvia, P. J., & Benedek, M. (2018) Scale development via network analysis: A comprehensive and concise measure of Openness to Experience PsyArXiv, 1-40.
1 2 3 4 5 6 | # Pearson's correlation only for CRAN checks
A <- TMFG(neoOpen, normal = FALSE)$A
nodes <- seq(1,48,2)
result <- network.coverage(A, nodes)
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