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

In centiserve: Find Graph Centrality Indices

Description

The score of node v, DMNC(v), is defined to be E/(N^epsilon):

|E(MNC(v))|/(|V(MNC(v))|^epsilon)

where for some 1 <= epsilon <= 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	ε parameter which default is 1.67.

Details

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

Value

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

Author(s)

Mahdi Jalili [e-mail]

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

g <- random.graph.game(20, 3/10)
dmnc(g)

Example output

Loading required package: igraph

Attaching package: 'igraph'

The following objects are masked from 'package:stats':

    decompose, spectrum

The following object is masked from 'package:base':

    union

Loading required package: Matrix
 [1] 0.10035001 0.15966418 0.15295591 0.15966418 0.31425334 0.00000000
 [7] 0.00000000 0.15966418 0.00000000 0.09875516 0.31932837 0.07757401
[13] 0.10035001 0.00000000 0.15052501 0.19751033 0.62850669 0.00000000
[19] 0.15966418 0.19751033

centiserve documentation built on May 2, 2019, 6:01 a.m.