def _predict_var(self, params, mu, prob_infl):
    'predict values for conditional variance V(endog | exog)\n\n        Parameters\n        ----------\n        params : array_like\n            The model parameters. This is only used to extract extra params\n            like dispersion parameter.\n        mu : array_like\n            Array of mean predictions for main model.\n        prob_inlf : array_like\n            Array of predicted probabilities of zero-inflation `w`.\n\n        Returns\n        -------\n        Predicted conditional variance.\n        '
    w = prob_infl
    var_ = (((1 - w) * mu) * (1 + (w * mu)))
    return var_
predict values for conditional variance V(endog | exog)

Parameters
----------
params : array_like
    The model parameters. This is only used to extract extra params
    like dispersion parameter.
mu : array_like
    Array of mean predictions for main model.
prob_inlf : array_like
    Array of predicted probabilities of zero-inflation `w`.

Returns
-------
Predicted conditional variance.
def _predict_var(self, params, mu, prob_infl):
    'predict values for conditional variance V(endog | exog)\n\n        Parameters\n        ----------\n        params : array_like\n            The model parameters. This is only used to extract extra params\n            like dispersion parameter.\n        mu : array_like\n            Array of mean predictions for main model.\n        prob_inlf : array_like\n            Array of predicted probabilities of zero-inflation `w`.\n\n        Returns\n        -------\n        Predicted conditional variance.\n        '
    w = prob_infl
    var_ = (((1 - w) * mu) * (1 + (w * mu)))
    return var_