dmnc: Find the density of maximum neighborhood component (DMNC) in a graph

Description

The score of node $v$, $DMNC(v)$, is defined to be $\frac{E}{N^{\epsilon}}$: $$\frac{\left|E(MNC(v))\right|}{\left|V(MNC(v))\right|^{\epsilon}}$$ where for some $1 \leq \epsilon \leq 2$.

Usage

dmnc(graph, vids = V(graph), mode = c("all", "out", "in"), epsilon = 1.67)

Arguments

graph

The input graph as igraph object

vids

Vertex sequence, the vertices for which the centrality values are returned. Default is all vertices.

mode

Character constatnt, it specifies how to use the direction of the edges if a directed graph is analyzed. For 'out' only the outgoing edges are followed. For 'in' all vertices from which the source vertex is reachable in at most order steps are counted. 'all' ignores the direction of the edges. This argument is ignored for undirected graphs.

epsilon

$\epsilon$ parameter which default is 1.67.

Value

A numeric vector contaning the centrality scores for the selected vertices.

Details

See Maximum Neighborhood Component (MNC) More detail at DMNC-Density of Maximum Neighborhood Component

References

Lin, Chung-Yen, et al. "Hubba: hub objects analyzer-a framework of interactome hubs identification for network biology." Nucleic acids research 36.suppl 2 (2008): W438-W443.

Examples

Run this code

# NOT RUN {
g <- random.graph.game(20, 3/10)
dmnc(g)
# }

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