Create a MLVSBM object from observed data

mlvsbm_create_network(
  X,
  A,
  directed = NULL,
  distribution = list("bernoulli", "bernoulli")
)

Arguments

X: A list of 2 squares binary matrices, the first one being the individual or lower level the second one being the organizational or upper level
A: A matrix the affiliation matrix with individuals in rows and organizations in columns
directed: A list of 2 boolean are the upper and lower level directed or not. Default will check if the matrix are symmetric or not.
distribution: A list for the distribution of X, only "bernoulli" is implemented

Value

An unfitted MLVSBM object corresponding to the multilevel network

Examples

ind_adj <- matrix(stats::rbinom(n = 10**2, size = 1, prob = .2),
                  nrow = 10, ncol = 10)
org_adj <- matrix(stats::rbinom(n = 10**2, size = 1, prob = .3),
                  nrow = 10, ncol = 10)
affiliation <- diag(1, 10)
my_mlvsbm <- mlvsbm_create_network(X = list(I = ind_adj, O = org_adj),
                                   directed = list(I = FALSE, O = FALSE),
                                   A = affiliation)