simulate_group_tna: Simulate sequences and fit a grouped TNA model

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

Simulate sequences and fit a grouped TNA model

Description

Simulate sequences and fit a grouped TNA model

Usage

simulate_group_tna(
  groups = 2L,
  actors = 50L,
  transitions = NULL,
  chain_length = 20L,
  initial = NULL,
  group_names = NULL,
  states = NULL,
  n_states = 5L,
  state_categories = c("metacognitive", "cognitive"),
  model = c("tna", "ftna", "ctna", "atna"),
  seed = NULL,
  ...,
  batch = NULL
)

Arguments

groups	Number of groups, defaulting to 2.
actors	Actors per group, scalar or one value per group, defaulting to 50.
transitions	A common transition matrix, one matrix per group, or NULL for randomly generated matrices. A tidy data frame with columns group, from, to and probability gives one matrix per group.
chain_length	Sequence length, defaulting to 20.
initial	Common initial probabilities, one vector per group, or NULL. A tidy data frame with columns group, state and probability gives one vector per group.
group_names	Optional group labels.
states, n_states, state_categories	State-space arguments passed to simulate_sequences().
model	TNA model type.
seed	Optional random seed. Group-specific deterministic offsets are used without leaking RNG state.
...	Advanced sequence arguments.
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 long-form simulab_sim base data.frame of grouped sequences with columns group, id, period, and state. as.data.frame(x, what = ) also returns true_transitions (the generating probabilities), estimated_edges (the fitted TNA weights), model_info, wide, and groups. The native group_tna model is accessible through as_tna_model(). Requires the suggested tna package.

Examples

if (requireNamespace("tna", quietly = TRUE)) {
  result <- simulate_group_tna(
    groups = 2, actors = 20, chain_length = 12, n_states = 3, seed = 1
  )
  head(result)
  components(result)

  # With no arguments, one transition matrix per group is drawn and fitted.
  drawn <- simulate_group_tna(seed = 1)
  as.data.frame(drawn, what = "true_transitions")
}

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