Comments (1)
That's possible using the StatsForecast.forecast_fitted_values
method. Here's an example:
from statsforecast.core import StatsForecast
from statsforecast.utils import AirPassengersDF as panel_df
from statsforecast.models import Naive
# Instantiate StatsForecast class
fcst = StatsForecast(df=panel_df,
models=[Naive(), AutoARIMA()],
freq='D', n_jobs=1)
# Access insample predictions
fcsts_df = fcst.forecast(h=12, fitted=True, level=(90, 10))
insample_fcsts_df = fcst.forecast_fitted_values()
insample_fcsts_df.tail(4)
from statsforecast.
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from statsforecast.