ntdeg

Degree and strength of each node

R

ntdeg(from, to, w = NULL, nodes = NULL, dir = FALSE)

A graph is an edge list: from[k] is tied to to[k]. The rules below hold for every network function in crimlab.

Parameters

from, to

Labels of the two ends of each edge: vectors of the same length (zero when nodes gives every node) with no missing values.

w

NULL, or one positive weight per edge (a tie’s strength, such as the number of co-offences).

nodes

NULL, or every node’s label once: the node order of the results and the way to include isolated nodes.

dir

TRUE for a directed graph (from sends a tie to to).

Returns

A data frame with one row per node: node, deg (distinct neighbours) and wdeg (summed weight); directed, node, in, out, deg (in + out), win, wout and wdeg. The degrees sum to twice the number of distinct edges: see proof("ntdeg").

Notes

• Nodes are identified by their labels, compared as text (as.character(); a factor by its labels, unused levels ignored). Results have one row per node, in the order nodes first appear: each edge’s from, then its to, edge by edge. With nodes, the order is that of nodes, which must hold every label of the edges once; labels in nodes that no edge names are isolated nodes.
• A self-loop (from[k] == to[k]) is dropped; its node stays.
• Repeated edges (the same pair, in either direction when undirected) are merged into one edge whose weight is the sum of their weights (1 each when w is NULL). So deg counts distinct neighbours and wdeg counts edges or their weight.
• A missing value in any argument is an error.

References

Wasserman, S. and Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. doi:10.1017/CBO9780511815478

Examples

ntdeg(c("a", "a", "b", "a"), c("b", "c", "c", "b"))
ntdeg(c("a", "a"), c("b", "c"), nodes = c("c", "b", "a", "z"), dir = TRUE)

Generated from the R help page: ntdeg in the R reference.