RegressionResults.get_prediction()
statsmodels.regression.linear_model.RegressionResults.get_prediction
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RegressionResults.get_prediction(exog=None, transform=True, weights=None, row_labels=None, **kwds)
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compute prediction results
Parameters: exog : array-like, optional
The values for which you want to predict.
transform : bool, optional
If the model was fit via a formula, do you want to pass exog through the formula. Default is True. E.g., if you fit a model y ~ log(x1) + log(x2), and transform is True, then you can pass a data structure that contains x1 and x2 in their original form. Otherwise, you’d need to log the data first.
weights : array_like, optional
Weights interpreted as in WLS, used for the variance of the predicted residual.
args, kwargs :
Some models can take additional arguments or keywords, see the predict method of the model for the details.
Returns: prediction_results : instance
The prediction results instance contains prediction and prediction variance and can on demand calculate confidence intervals and summary tables for the prediction of the mean and of new observations.
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.regression.linear_model.RegressionResults.get_prediction.html