VARReduce

Generalized VAR forecaster using tabularized regression.

Quickstart

from sktime.forecasting.var_reduce import VARReduce

estimator = VARReduce(lags=1, regressor=None)

Parameters(2)

lagsint, optional, default=1

The number of lagged values to include in the model.

regressorobject, optional (default=LinearRegression())

The regressor to use for fitting the model. Must be scikit-learn-compatible.

Examples

>>> from sktime.forecasting.var_reduce import VARReduce
>>> from sklearn.linear_model import Lasso
>>> from sktime.datasets import load_longley
>>> _, y = load_longley ()
>>> forecaster = VARReduce (regressor = Lasso ())
>>> forecaster. fit (y) VARReduce(
... )
>>> y_pred = forecaster. predict (fh = [1, 2, 3 ])