simulate_multiplex_network: Simulate a multiplex network

In simulab: Simulates a Wide Variety of Data Shapes, Sizes and Distributions

Simulate a multiplex network

Description

Simulate a multiplex network

Usage

simulate_multiplex_network(
  nodes,
  layers,
  edges = NULL,
  probability = 0.1,
  directed = TRUE,
  loops = FALSE,
  weight = c("binary", "uniform", "normal", "poisson"),
  weight_mean = 1,
  weight_sd = 1,
  weight_range = c(0.1, 1),
  node_type = NULL,
  seed = NULL,
  batch = NULL
)

Arguments

nodes	Number of nodes or unique labels shared across layers.
layers	Number of layers or unique layer labels.
edges	Optional exact edge count, scalar or one value per layer.
probability	Edge probability, scalar or one value per layer.
directed	Generate directed edges.
loops	Permit self-loops.
weight	Edge-weight distribution.
weight_mean, weight_sd, weight_range	Weight parameters.
node_type	Optional node type for each node.
seed	Optional base seed; layers use deterministic offsets.
batch	Optional single positive whole number. When given, the simulator runs batch times and returns a plain list of batch results, each exactly what the same call without batch returns. With a seed, every dataset gets its own seed drawn from seed, so the whole batch is reproducible; without one the datasets are consecutive draws from the session's random-number stream. The default NULL returns a single result.

Value

A tidy layered edge-list simulab_sim base data.frame with one row per edge and columns layer, from, to, and weight. Every layer is drawn independently over the same node set. as.data.frame(x, what = ) also returns nodes (node, type), layers (layer, probability), adjacency (a long layer/row/column/weight table over all ordered node pairs in every layer), and a one-row settings table.

Examples

result <- simulate_multiplex_network(nodes = 25, layers = 3, probability = 0.1, seed = 1)
head(result)
components(result)

simulab documentation built on Oct. 15, 2026, 5:08 p.m.