GLMResults.get_prediction(exog=None, exposure=None, offset=None, transform=True, which=None, linear=None, average=False, agg_weights=None, row_labels=None)[source]

Compute prediction results for GLM compatible models.

Options and return class depend on whether “which” is None or not.

exogarray_like, optional

The values for which you want to predict.

exposurearray_like, optional

Exposure time values, only can be used with the log link function.

offsetarray_like, optional

Offset values.

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.

which‘mean’, ‘linear’, ‘var’(optional)

Statitistic to predict. Default is ‘mean’. If which is None, then the deprecated keyword “linear” applies. If which is not None, then a generic Prediction results class will be returned. Some options are only available if which is not None. See notes.

  • ‘mean’ returns the conditional expectation of endog E(y | x), i.e. inverse of the model’s link function of linear predictor.

  • ‘linear’ returns the linear predictor of the mean function.

  • ‘var_unscaled’ variance of endog implied by the likelihood model. This does not include scale or var_weights.


The linear` keyword is deprecated and will be removed, use ``which keyword instead. If which is None, then the linear keyword is used, otherwise it will be ignored. If True and which is None, the linear predicted values are returned. If False or None, then the statistic specified by which will be returned.


Keyword is only used if which is not None. If average is True, then the mean prediction is computed, that is, predictions are computed for individual exog and then the average over observation is used. If average is False, then the results are the predictions for all observations, i.e. same length as exog.

agg_weightsndarray, optional

Keyword is only used if which is not None. Aggregation weights, only used if average is True.

row_labelslist of str or None

If row_lables are provided, then they will replace the generated labels.

prediction_resultsinstance of a PredictionResults class.

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. The Results class of the return depends on the value of which.


Changes in statsmodels 0.14: The which keyword has been added. If which is None, then the behavior is the same as in previous versions, and returns the mean and linear prediction results. If the which keyword is not None, then a generic prediction results class is returned and is not backwards compatible with the old prediction results class, e.g. column names of summary_frame differs. There are more choices for the returned predicted statistic using which. More choices will be added in the next release. Two additional keyword, average and agg_weights options are now also available if which is not None. In a future version which will become not None and the backwards compatible prediction results class will be removed.