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
- y{
Notes
Lütkepohl pp. 39-40
Last update:
Dec 16, 2024