defineSBM: Define a network

In GrossSBM/sbm: Stochastic Blockmodels

Description

Define a network

Usage

defineSBM(
  netMat,
  model = "bernoulli",
  type = ifelse(ncol(netMat) == nrow(netMat), "simple", "bipartite"),
  directed = !isSymmetric(netMat),
  dimLabels = c(row = "row", col = "col"),
  covariates = list()
)

Arguments

netMat	a matrix describing the network: either an adjacency (square) or incidence matrix with possibly weighted entries.
model	character describing the model for the relation between nodes ('bernoulli', 'poisson', 'gaussian', ...). Default is 'bernoulli'.
type	Type of the matrix, choice between 'simple' and 'bipartite'
directed	logical: is the network directed or not? Only relevant when type is 'Simple'. Default is TRUE if netMat is symmetric, FALSE otherwise
dimLabels	an optional list of labels for each dimension (in row, in column)
covariates	a list of matrices with same dimension as mat describing covariates at the edge level. No covariate per Default.

Value

an object SimpleSBM or BipartiteSBM with the informations required to define a future multipartite network

Examples

A <- matrix(rbinom(100,1,.2), 10, 10)
myNet <- defineSBM(A, "poisson", "simple", TRUE, "Actor")

GrossSBM/sbm documentation built on April 8, 2021, 5:53 a.m.