def _predict_precision(self, params, exog_precision=None):
    'Predict values for precision function for given exog_precision.\n\n        Parameters\n        ----------\n        params : array_like\n            The model parameters.\n        exog_precision : array_like\n            Array of predictor variables for precision.\n\n        Returns\n        -------\n        Predicted precision.\n        '
    if (exog_precision is None):
        exog_precision = self.exog_precision
    k_mean = self.exog.shape[1]
    params_precision = params[k_mean:]
    linpred_prec = np.dot(exog_precision, params_precision)
    phi = self.link_precision.inverse(linpred_prec)
    return phi
Predict values for precision function for given exog_precision.

Parameters
----------
params : array_like
    The model parameters.
exog_precision : array_like
    Array of predictor variables for precision.

Returns
-------
Predicted precision.
def _predict_precision(self, params, exog_precision=None):
    'Predict values for precision function for given exog_precision.\n\n        Parameters\n        ----------\n        params : array_like\n            The model parameters.\n        exog_precision : array_like\n            Array of predictor variables for precision.\n\n        Returns\n        -------\n        Predicted precision.\n        '
    if (exog_precision is None):
        exog_precision = self.exog_precision
    k_mean = self.exog.shape[1]
    params_precision = params[k_mean:]
    linpred_prec = np.dot(exog_precision, params_precision)
    phi = self.link_precision.inverse(linpred_prec)
    return phi