statsmodels.tsa.arima_model.ARIMA.predict¶
-
ARIMA.
predict
(params, start=None, end=None, exog=None, typ='linear', dynamic=False)[source]¶ ARIMA model in-sample and out-of-sample prediction
- Parameters
- paramsarray_like
The fitted parameters of the model.
- start
int
,str
,or
datetime
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.
- end
int
,str
,or
datetime
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.
- exogarray_like,
optional
If the model is an ARMAX and out-of-sample forecasting is requested, exog must be given. exog must be aligned so that exog[0] is used to produce the first out-of-sample forecast. The number of observation in exog should match the number of out-of-sample forecasts produced. If the length of exog does not match the number of forecasts, a SpecificationWarning is produced.
- dynamicbool,
optional
The dynamic keyword affects in-sample prediction. If dynamic is False, then the in-sample lagged values are used for prediction. If dynamic is True, then in-sample forecasts are used in place of lagged dependent variables. The first forecast value is start.
- typ
str
{‘linear’, ‘levels’} ‘linear’ : Linear prediction in terms of the differenced endogenous variables.
‘levels’ : Predict the levels of the original endogenous variables.
- Returns
- predict
ndarray
The predicted values.
- predict
Notes
Use the results predict method instead.