CountResults.predict()

statsmodels.discrete.discrete_model.CountResults.predict

CountResults.predict(exog=None, transform=True, *args, **kwargs)

Call self.model.predict with self.params as the first argument.

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. args, kwargs : : Some models can take additional arguments or keywords, see the predict method of the model for the details.

Returns:

prediction : ndarray or pandas.Series See self.model.predict