influential (version 1.1.2)

ivi.from.indices: Integrated Value of Influence (IVI)

Description

This function calculates the IVI of the desired nodes from previously calculated centrality measures. This function is not dependent to other packages and the required centrality measures, namely degree centrality, ClusterRank, betweenness centrality, Collective Influence, local H-index, and neighborhood connectivity could have been calculated by any means beforehand.

Usage

ivi.from.indices(DC, CR, LH_index, NC, BC, CI, scaled = TRUE)

Arguments

DC

A vector containing the values of degree centrality of the desired vertices.

CR

A vector containing the values of ClusterRank of the desired vertices.

LH_index

A vector containing the values of local H-index of the desired vertices.

NC

A vector containing the values of neighborhood connectivity of the desired vertices.

BC

A vector containing the values of betweenness centrality of the desired vertices.

CI

A vector containing the values of Collective Influence of the desired vertices.

scaled

Logical; whether the end result should be 1-100 range normalized or not (default is TRUE).

Value

A numeric vector with the IVI values based on the provided centrality measures.

See Also

ivi, exir

Other integrative ranking functions: exir(), hubness.score(), ivi(), spreading.score()

Examples

# NOT RUN {
MyData <- centrality.measures
My.vertices.IVI <- ivi.from.indices(DC = centrality.measures$DC,
                                    CR = centrality.measures$CR,
                                    NC = centrality.measures$NC,
                                    LH_index = centrality.measures$LH_index,
                                    BC = centrality.measures$BC,
                                    CI = centrality.measures$CI)
# }