start : int, str, or datetime, optional
Zero-indexed observation number at which to start forecasting, ie.,
the first forecast is start. Can also be a date string to
parse or a datetime type. Default is the the zeroth observation.
end : int, str, or datetime, optional
Zero-indexed observation number at which to end forecasting, ie.,
the first forecast is start. Can also be a date string to
parse or a datetime type. However, if the dates index does not
have a fixed frequency, end must be an integer index if you
want out of sample prediction. Default is the last observation in
the sample.
exog : array_like, optional
If the model includes exogenous regressors, you must provide
exactly enough out-of-sample values for the exogenous variables if
end is beyond the last observation in the sample.
dynamic : boolean, int, str, or datetime, optional
Integer offset relative to start at which to begin dynamic
prediction. Can also be an absolute date string to parse or a
datetime type (these are not interpreted as offsets).
Prior to this observation, true endogenous values will be used for
prediction; starting with this observation and continuing through
the end of prediction, forecasted endogenous values will be used
instead.
kwargs :
Additional arguments may required for forecasting beyond the end
of the sample. See FilterResults.predict for more details.
|