initparamtheta(
    initial_smoothed: float,
    alpha: float,
    theta: float,
    y: ndarray,
    modeltype: ModelType
)

switch_theta(model: str) → ModelType

optimize_theta_target_fn(
    init_par: dict[str, float],
    optimize_params: dict[str, bool],
    y: ndarray,
    modeltype: ModelType,
    nmse: int
)

thetamodel(
    y: ndarray,
    m: int,
    modeltype: str,
    initial_smoothed: float,
    alpha: float,
    theta: float,
    nmse: int
)

compute_pi_samples(
    n,
    h,
    states,
    sigma,
    alpha,
    theta,
    mean_y,
    seed=0,
    n_samples=200
)

forecast_theta(obj, h, level=None)

auto_theta(
    y,
    m,
    model=None,
    initial_smoothed=None,
    alpha=None,
    theta=None,
    nmse=3,
    decomposition_type='multiplicative'
)

forward_theta(fitted_model, y)