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statsmodels.tsa.ar_model.ARResults.predict

ARResults.predict(start=None, end=None, method='static')[source]

Returns in-sample prediction or forecasts.

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.

method : string {‘dynamic’, ‘static’}

If method is ‘dynamic’, then fitted values are used in place of observed ‘endog’ to make forecasts. If ‘static’, observed ‘endog’ are used. Only ‘static’ is currently implemented.

confint : bool, float

Whether to return confidence intervals. If confint == True, 95 % confidence intervals are returned. Else if confint 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.

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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