statsmodels.tsa.vector_ar.var_model.VARProcess.forecast_interval¶

VARProcess.forecast_interval(y, steps, alpha=0.05, exog_future=None)[source]¶

Construct forecast interval estimates assuming the y are Gaussian

Parameters:¶

y : {ndarray, None}¶

The initial values to use for the forecasts. If None, the last k_ar values of the original endogenous variables are used.

steps : int¶

Number of steps ahead to forecast

alpha : float, optional¶

The significance level for the confidence intervals.

exog_future : ndarray, optional¶

Forecast values of the exogenous variables. Should include constant, trend, etc. as needed, including extrapolating out of sample.

Returns:¶

• point (ndarray) – Mean value of forecast

• lower (ndarray) – Lower bound of confidence interval

• upper (ndarray) – Upper bound of confidence interval

Notes

Lütkepohl pp. 39-40