met.geodesic: Geodesic distances
In SebastianSosa/ANTs: Animal Network Toolkit Software

met.geodesic

R Documentation

Geodesic distances

Description

Calculates the geodesic distances of a network.

Usage

met.geodesic(
  M,
  weighted = TRUE,
  shortest.weight = FALSE,
  normalization = TRUE,
  directed = TRUE,
  out = TRUE
)

Arguments

`M`	a square adjacency matrix, or a list of square adjacency matrices, or an output of ANT functions stat.ds.grp, stat.df.focal, stat.net.lk.
`weighted`	if true, it binarizes the square adjacency matrix M. Geodesic distances and diameter are based only on the presence or absence of edges.
`shortest.weight`	if false, it considers the highest met.strength as the shortest path.
`normalization`	normalizes the weights of the links i.e. divides them by the average strength of the network. Argument normalization can't be TRUE when argument weighted is FALSE.
`directed`	if false, then it symmetrizes the matrix. Otherwise, it calculates geodesic distances and diameter according to the directionality of the links.
`out`	if true, it considers outgoing ties.

Details

Binary network met.density is the ratio of existing links of a network in relation to all potential links.

Value

a matrix representing the geodesic distances of the network if argument M is a square matrix.
A list of matrices if argument M is a list of matrices. Each matrix represents the geodesic distances of the corresponding matrix of the list.

Author(s)

Sebastian Sosa, Ivan Puga-Gonzalez.

References

Doreian, P. (1974). On the connectivity of social networks. Journal of Mathematical Sociology, 3(2), 245-258.

Burt, R. S. (1976). Positions in networks. Social forces, 55(1), 93-122.

Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social networks, 32(3), 245-251.

Sosa, S. (2018). Social Network Analysis, in: Encyclopedia of Animal Cognition and Behavior. Springer.