met.geodesic {ANTs} 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.

### Examples

met.geodesic(sim.m)


[Package ANTs version 0.0.16 Index]