Generalized k-core — k

Generalized k-core for undirected, directed, weighted and multilevel networks

Usage

k_core(
  A,
  B1 = NULL,
  multilevel = FALSE,
  type = "in",
  digraph = FALSE,
  loops = FALSE,
  weighted = FALSE,
  alpha = 1
)

Arguments

A: A matrix object.
B1: An incidence matrix for multilevel networks.
multilevel: Whether the measure of k-core is for multilevel networks.
type: Character string, “out” (outdegree), “in” (indegree) and “all” (degree)
digraph: Whether the matrix is directed or undirected
loops: Whether the diagonal of the matrix is considered or not
weighted: Whether the measure of k-core is for valued matrices
alpha: Sets the alpha parameter in the generalised measures from Opsahl et al. (2010)

Value

This function return the k-core.

References

Batagelj, V., & Zaveršnik, M. (2011). Fast algorithms for determining (generalized) core groups in social networks. Advances in Data Analysis and Classification, 5(2), 129–145. https://doi.org/10.1007/s11634-010-0079-y

Eidsaa, M., & Almaas, E. (2013). s-core network decomposition: A generalization of $k$-core analysis to weighted networks. Physical Review E, 88(6), 062819. https://doi.org/10.1103/PhysRevE.88.062819

Seidman S (1983). 'Network structure and minimum degree'. Social Networks, 5, 269-287.

Author

Alejandro Espinosa-Rada

Examples


A1 <- matrix(c(
  0, 1, 0, 0, 0,
  1, 0, 0, 1, 0,
  0, 0, 0, 1, 0,
  0, 1, 1, 0, 1,
  0, 0, 0, 1, 0
), byrow = TRUE, ncol = 5)
B1 <- matrix(c(
  1, 0, 0,
  1, 1, 0,
  0, 1, 0,
  0, 1, 0,
  0, 1, 1
), byrow = TRUE, ncol = 3)

k_core(A1, B1, multilevel = TRUE)
#> [1] 1 2 1 2 2