statsmodels.discrete.count_model.ZeroInflatedGeneralizedPoisson.predict

ZeroInflatedGeneralizedPoisson.predict(params, exog=None, exog_infl=None, exposure=None, offset=None, which='mean')

Predict response variable of a count model given exogenous variables.

Parameters:

• params (array-like) – The parameters of the model
• exog (array, optional) – A reference to the exogenous design. If not assigned, will be used exog from fitting.
• exog_infl (array, optional) – A reference to the zero-inflated exogenous design. If not assigned, will be used exog from fitting.
• offset (array, optional) – Offset is added to the linear prediction with coefficient equal to 1.
• exposure (array, optional) – Log(exposure) is added to the linear prediction with coefficient equal to 1. If exposure is specified, then it will be logged by the method. The user does not need to log it first.
• which (string, optional) – Define values that will be predicted. ‘mean’, ‘mean-main’, ‘linear’, ‘mean-nonzero’, ‘prob-zero, ‘prob’, ‘prob-main’ Default is ‘mean’.

Notes