econirl.simulation.simulate_panel

econirl.simulation.simulate_panel(env, n_individuals=100, n_periods=100, seed=None, use_optimal_policy=True, policy=None)[source]

Simulate panel data from a DDC environment.

Generates synthetic data by simulating the decision process for multiple individuals over multiple time periods.

Parameters:

  • env (DDCEnvironment) – DDCEnvironment with true parameters

  • n_individuals (int) – Number of individuals to simulate

  • n_periods (int) – Number of time periods per individual

  • seed (int | None) – Random seed for reproducibility

  • use_optimal_policy (bool) – If True, compute optimal policy from true params

  • policy (Array | None) – Pre-computed policy to use (overrides use_optimal_policy)

Returns:

Panel object with simulated trajectories

Return type:

TrajectoryPanel

Example

>>> env = RustBusEnvironment(operating_cost=0.001, replacement_cost=3.0)
>>> panel = simulate_panel(env, n_individuals=500, n_periods=100, seed=42)
>>> print(f"Generated {panel.num_observations} observations")