degree: Degree of the vertices

In influential: Identification and Classification of the Most Influential Nodes

Degree of the vertices

Description

This function and all of its descriptions have been obtained from the igraph package.

Usage

degree(
  graph,
  v = V(graph),
  mode = c("all", "out", "in", "total"),
  loops = TRUE,
  normalized = FALSE
)

Arguments

graph	The graph to analyze (an igraph graph).
v	The ids of vertices of which the degree will be calculated.
mode	Character string, “out” for out-degree, “in” for in-degree or “total” for the sum of the two. For undirected graphs this argument is ignored. “all” is a synonym of “total”.
loops	Logical; whether the loop edges are also counted. If the graph has a weight edge attribute, then this is used by default. Weights are used to calculate weighted shortest paths, so they are interpreted as distances.
normalized	Logical scalar, whether to normalize the degree. If TRUE then the result is divided by n-1, where n is the number of vertices in the graph.

Value

A numeric vector of the same length as argument v.

See Also

ivi, cent_network.vis, and degree for a complete description on this function

Other centrality functions: betweenness(), clusterRank(), collective.influence(), h_index(), lh_index(), neighborhood.connectivity(), sirir()

Examples

## Not run: 
MyData <- coexpression.data
My_graph <- graph_from_data_frame(MyData)
GraphVertices <- V(My_graph)
My_graph_degree <- degree(My_graph, v = GraphVertices, normalized = FALSE)

## End(Not run)

influential documentation built on Nov. 19, 2023, 9:06 a.m.