def _predict_var(self, params, exog=None, exog_precision=None):
    'predict values for conditional variance V(endog | exog)\n\n        Parameters\n        ----------\n        params : array_like\n            The model parameters.\n        exog : array_like\n            Array of predictor variables for mean.\n        exog_precision : array_like\n            Array of predictor variables for precision.\n\n        Returns\n        -------\n        Predicted conditional variance.\n        '
    mean = self.predict(params, exog=exog)
    precision = self._predict_precision(params, exog_precision=exog_precision)
    var_endog = ((mean * (1 - mean)) / (1 + precision))
    return var_endog
predict values for conditional variance V(endog | exog)

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

Returns
-------
Predicted conditional variance.
def _predict_var(self, params, exog=None, exog_precision=None):
    'predict values for conditional variance V(endog | exog)\n\n        Parameters\n        ----------\n        params : array_like\n            The model parameters.\n        exog : array_like\n            Array of predictor variables for mean.\n        exog_precision : array_like\n            Array of predictor variables for precision.\n\n        Returns\n        -------\n        Predicted conditional variance.\n        '
    mean = self.predict(params, exog=exog)
    precision = self._predict_precision(params, exog_precision=exog_precision)
    var_endog = ((mean * (1 - mean)) / (1 + precision))
    return var_endog