met.geodesic {ANTs} | R Documentation |
Calculates the geodesic distances of a network.
met.geodesic(
M,
weighted = TRUE,
shortest.weight = FALSE,
normalization = TRUE,
directed = TRUE,
out = TRUE
)
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. |
Binary network met.density is the ratio of existing links of a network in relation to all potential links.
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.
Sebastian Sosa, Ivan Puga-Gonzalez.
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.
met.geodesic(sim.m)