Simulate null-model networks from a netify object

Generates nsim new netify objects from one of three standard null models, holding the actor set fixed (and, where applicable, the observed density / degree sequence). Useful for sanity-checking whether an observed network statistic (transitivity, modularity, etc.) is surprising relative to a chance benchmark, without reaching for statnet::ergm for a simple null.

Usage

# S3 method for class 'netify'
simulate(
  object,
  nsim = 1L,
  seed = NULL,
  model = c("erdos_renyi", "configuration", "dyad_permutation"),
  ...
)

Arguments

object

A netify object (cross-sectional or per-period; for longitudinal input each period is simulated independently).

nsim

Integer. Number of simulated draws to return.

seed

Optional integer. Local RNG seed; the user's global set.seed() stream is left untouched.

model

Character. One of:

"erdos_renyi"

Independent Bernoulli edges matched to the observed density (and directedness).

"configuration"

Configuration-model rewire that preserves the observed degree sequence (in/out for directed inputs). Uses igraph::sample_degseq().

"dyad_permutation"

Permute dyads (Snijders-Borgatti vertex relabel + symmetric reshuffle). Preserves density and, conditional on permutation symmetry, degree distribution shape.

...

Passed to the underlying model implementation.

Value

A list of length nsim of netify objects with the same class / mode / symmetry as the input.

Author

Cassy Dorff, Shahryar Minhas