decay: Find the decay centrality of a given vertex

Description Usage Arguments Details Value Author(s) References Examples

Description

Decay centrality of a given vertex x of a graph G is define as:

sum(sigma ^ d(x,y), y in V(G))

where d(x,y) denotes the distance between x and y and sigma in (0,1) is a parameter.

Usage

1
2
decay(graph, vids = V(graph), mode = c("all", "out", "in"),
  weights = NULL, decay = 0.5)

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 constant, gives whether the shortest paths to or from the given vertices should be calculated for directed graphs. If out then the shortest paths from the vertex, if in then to it will be considered. If all, the default, then the corresponding undirected graph will be used, ie. not directed paths are searched. This argument is ignored for undirected graphs.

weights

Possibly a numeric vector giving edge weights. If this is NULL, the default, and the graph has a weight edge attribute, then the attribute is used. If this is NA then no weights are used (even if the graph has a weight attribute).

decay

A decay parameter which the default is 0.5.

Details

Decay centrality is a centrality measure based on the proximity between a choosen vertex and every other vertex weighted by the decay.
More detail at Decay Centrality

Value

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

Author(s)

Mahdi Jalili m_jalili@farabi.tums.ac.ir

References

Jana Hurajova, Silvia Gago and Tomas Madaras, Decay Centrality, 15th Conference of Kosice Mathematicians. Herl'ny 2.-5. aprila 2014.

Examples

1
2
g <- graph(c(1,2,2,3,3,4,4,2), directed=FALSE)
decay(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] 2.00 2.50 2.25 2.25

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