statsmodels.tsa.ar_model.ARResults.predict
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ARResults.predict(start=None, end=None, dynamic=False)
[source] -
Returns in-sample and out-of-sample prediction.
Parameters: 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.
dynamic : bool
The
dynamic
keyword affects in-sample prediction. If dynamic is False, then the in-sample lagged values are used for prediction. Ifdynamic
is True, then in-sample forecasts are used in place of lagged dependent variables. The first forecastedconfint : bool, float
Whether to return confidence intervals. If
confint
== True, 95 % confidence intervals are returned. Else ifconfint
is a float, then it is assumed to be the alpha value of the confidence interval. That is confint == .05 returns a 95% confidence interval, and .10 would return a 90% confidence interval. value isstart
.Returns: predicted values : array
Notes
The linear Gaussian Kalman filter is used to return pre-sample fitted values. The exact initial Kalman Filter is used. See Durbin and Koopman in the references for more information.
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