bayespecon.dgp.simulate_panel_dlm_fe¶

bayespecon.dgp.simulate_panel_dlm_fe(N, T, phi=0.4, beta=None, sigma=1.0, sigma_alpha=0.5, err_hetero=False, rng=None, seed=None, W=None, gdf=None, contiguity='queen', create_gdf=False, geometry_type='polygon', wide=False)[source]¶

Simulate dynamic non-spatial panel FE data.

DGP¶

y_t = phi y_{t-1} + X_t beta + alpha + eps_t.

param N:

Number of units and time periods.

type N:

int

param T:

Number of units and time periods.

type T:

int

param phi:

Dynamic autoregressive coefficient on lagged dependent variable.

type phi:

float, default=0.4

param beta:

Coefficients including intercept.

type beta:

np.ndarray, optional

param sigma:

Idiosyncratic noise scale.

type sigma:

float, default=1.0

param sigma_alpha:

Unit effect scale.

type sigma_alpha:

float, default=0.5

param err_hetero:

If True, generate heteroskedastic innovations with observation-specific standard deviations \(\sigma_i = \sigma \sqrt{1 + \|x_{it}\|^2}\) per period.

type err_hetero:

bool, default=False

param rng:

Random state controls.

param seed:

Random state controls.

param W:

Optional spatial structure inputs retained for API consistency.

param gdf:

Optional spatial structure inputs retained for API consistency.

param contiguity:

Optional spatial structure inputs retained for API consistency.

returns:

Includes time-first stacked arrays and panel index columns.

rtype:

dict