Identification and Classification of the Most Influential Nodes


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Documentation for package ‘influential’ version 2.2.9

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BC Vertex betweenness centrality
betweenness Vertex betweenness centrality
centrality.measures Centrality measures dataset
cent_network.vis Centrality-based network visualization
CI Collective Influence (CI)
clusterRank ClusterRank (CR)
coexpression.adjacency Adjacency matrix
coexpression.data Co-expression dataset
collective.influence Collective Influence (CI)
comp_manipulate Computational manipulation of cells
cond.prob.analysis Conditional probability of deviation from means
CPA Conditional probability of deviation from means
CR ClusterRank (CR)
DCA Assessment of innate features and associations of two network centrality measures (dependent and independent)
DCANR Assessment of innate features and associations of two network centrality measures
DDA Assembling the differential/regression data
diff_data.assembly Assembling the differential/regression data
double.cent.assess Assessment of innate features and associations of two network centrality measures (dependent and independent)
double.cent.assess.noRegression Assessment of innate features and associations of two network centrality measures
ExIR Experimental data-based Integrated Ranking
exir Experimental data-based Integrated Ranking
exir.vis Visualization of ExIR results
fcor Fast correlation and mutual rank analysis
h.index H-index
hubness.score Hubness score
h_index H-index
IVI Integrated Value of Influence (IVI)
ivi Integrated Value of Influence (IVI)
IVI.FI Integrated Value of Influence (IVI)
ivi.from.indices Integrated Value of Influence (IVI)
lh.index local H-index (LH-index)
lh_index local H-index (LH-index)
NC Neighborhood connectivity
neighborhood.connectivity Neighborhood connectivity
runShinyApp Run shiny app
sif2igraph SIF to igraph
SIRIR SIR-based Influence Ranking
sirir SIR-based Influence Ranking
spreading.score Spreading score