- GLMResults.get_prediction(exog=None, exposure=None, offset=None, transform=True, linear=False, row_labels=None)¶
Compute prediction results for GLM compatible models.
The values for which you want to predict.
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.
If row_lables are provided, then they will replace the generated labels.
Instance of linear prediction results used for confidence intervals based on endpoint transformation.
If no link function is provided, then the model.family.link is used.
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.