statsmodels.regression.linear_model.OLSResults.get_prediction¶
-
OLSResults.get_prediction(exog=
None, transform=True, weights=None, row_labels=None, **kwargs)¶ 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.
- row_labels : list¶
A list of row labels to use. If not provided, read exog is available.
- **kwargs¶
Some models can take additional keyword arguments, see the predict method of the model for the details.
- Returns:¶
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.
- Return type:¶