gen_density: Generalized density

In anespinosa/netmem: Social Network Measures using Matrices

Generalized density

Description

Generalized density

Usage

gen_density(
  A,
  directed = TRUE,
  bipartite = FALSE,
  loops = FALSE,
  weighted = FALSE,
  multilayer = FALSE
)

Arguments

A	A symmetric or incidence matrix object
directed	Whether the matrix is directed
bipartite	Whether the matrix is bipartite
loops	Whether to consider the loops
weighted	Whether the matrix is weighted
multilayer	Whether the matrix is multilayer (i.e., multiplex and/or multilevel)

Value

This function returns the density of the matrix(es)

Author(s)

Alejandro Espinosa-Rada

References

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

Examples

# A bipartite matrix
B <- matrix(c(
  1, 1, 0,
  0, 0, 1,
  0, 1, 1,
  0, 0, 1
), byrow = TRUE, ncol = 3)
gen_density(B, bipartite = TRUE)

# A multilevel network
A1 <- matrix(c(
  0, 1, 0, 0, 1,
  1, 0, 0, 1, 1,
  0, 0, 0, 1, 1,
  0, 1, 1, 0, 1,
  1, 1, 1, 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)

A2 <- matrix(c(
  0, 1, 1,
  1, 0, 0,
  1, 0, 0
), byrow = TRUE, nrow = 3)

B2 <- matrix(c(
  1, 1, 0, 0,
  0, 0, 1, 0,
  0, 0, 1, 1
), byrow = TRUE, ncol = 4)

A3 <- matrix(c(
  0, 1, 3, 1,
  1, 0, 0, 0,
  3, 0, 0, 5,
  1, 0, 5, 0
), byrow = TRUE, ncol = 4)

matrices <- list(A1, B1, A2, B2, A3)
gen_density(matrices, multilayer = TRUE)

# A multiplex network
A <- matrix(c(
  0, 1, 3, 6, 4,
  2, 0, 4, 5, 2,
  4, 1, 0, 6, 1,
  5, 6, 3, 0, 6,
  1, 1, 2, 3, 0
), byrow = TRUE, ncol = 5)
gen_density(A, multilayer = TRUE)

anespinosa/netmem documentation built on April 5, 2025, 5:02 p.m.