If an integer, the number of steps to forecast from the end of the sample. Can also be a date string to parse or a datetime type. However, if the dates index does not have a fixed frequency, steps must be an integer. Default is 1.
Whether to compute forecasts of only the “signal” component of the observation equation. Default is False. For example, the observation equation of a time-invariant model is \(y_t = d + Z \alpha_t + \varepsilon_t\), and the “signal” component is then \(Z \alpha_t\). If this argument is set to True, then forecasts of the “signal” \(Z \alpha_t\) will be returned. Otherwise, the default is for forecasts of \(y_t\) to be returned.
Additional arguments may required for forecasting beyond the end of the sample. See FilterResults.predict for more details.
Out-of-sample forecasts (Numpy array or Pandas Series or DataFrame, depending on input and dimensions). Dimensions are (steps x k_endog).
In-sample predictions and out-of-sample forecasts.
Out-of-sample forecasts and results including confidence intervals.
In-sample predictions / out-of-sample forecasts and results including confidence intervals.