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. if supplied, sets a local rng seed and restores the user's global set.seed() stream afterward. if NULL, simulation uses and advances the current rng stream normally.

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