smooth.SMA.predict_intervals

SMA.predict_intervals(h, X=None, levels=[0.8, 0.95], side='both', nsim=10000)

Generate prediction intervals using the fitted ADAM model.

Convenience wrapper around predict() that defaults to interval="prediction" and accepts multiple confidence levels.

Parameters:

  • h (int) – Forecast horizon (number of steps to forecast).

  • X (Optional[NDArray]) – Exogenous variables for the forecast period.

  • levels (List[float]) – Confidence levels for prediction intervals. Each level produces a pair of lower/upper columns in the output DataFrame. For example, levels=[0.8, 0.95] with side="both" yields columns "lower_0.1", "lower_0.025", "upper_0.9", "upper_0.975".

  • side (Literal['both', 'upper', 'lower']) – Which side(s) of the intervals to return.

  • nsim (int) – Number of simulations for simulation-based intervals.

Returns:

Structured result with .mean, .lower, .upper attributes.

Return type:

ForecastResult

Parent Class: SMA