statsmodels.regression.linear_model.OLSResults.get_prediction¶
- OLSResults.get_prediction(exog=None, transform=True, weights=None, row_labels=None, **kwargs)¶
Compute prediction results.
- Parameters:
- exogarray_like,
optional The values for which you want to predict.
- transformbool,
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.
- weightsarray_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.
- exogarray_like,
- Returns:
linear_model.PredictionResultsThe 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.