ForecastKnownValues

Forecaster that plays back known or prescribed values as forecasts.

Quickstart

from sktime.forecasting.dummy import ForecastKnownValues

estimator = ForecastKnownValues(y_known, method=None, fill_value=None, limit=None)

Parameters(4)

y_knownpd.DataFrame or pd.Series in one of the sktime compatible data formats

should contain known values that the forecaster will replay in predict can also be in a non-pandas sktime data format, will then be coerced to pandas

methodstr or None, optional, default=None

one of {None, ‘backfill’/’bfill’, ‘pad’/’ffill’, ‘nearest’} method to use for imputing indices at which forecasts are unavailable in y_known

fill_valuescalar, optional, default=np.NaN

value to use for any missing values (e.g., if method is None)

limitint, optional, default=None=infinite

maximum number of consecutive elements to bfill/ffill if method=bfill/ffill

Examples

>>> import pandas as pd
>>> y_known = pd. DataFrame (range (100))
>>> y_train = y_known [: 24 ]
>>> 
>>> from sktime.forecasting.dummy import ForecastKnownValues
>>> 
>>> fcst = ForecastKnownValues (y_known)
>>> fcst. fit (y_train, fh = [1, 2, 3 ]) ForecastKnownValues(
... ) The forecast “plays back” the known/prescribed values from y_known
>>> y_pred = fcst. predict ()