@classmethod
def from_formula(cls, formula, data, exog_precision_formula=None, *args, **kwargs):
    if (exog_precision_formula is not None):
        if ('subset' in kwargs):
            d = data.ix[kwargs['subset']]
            Z = patsy.dmatrix(exog_precision_formula, d)
        else:
            Z = patsy.dmatrix(exog_precision_formula, data)
        kwargs['exog_precision'] = Z
    return super(BetaModel, cls).from_formula(formula, data, *args, **kwargs)
@classmethod
def from_formula(cls, formula, data, exog_precision_formula=None, *args, **kwargs):
    if (exog_precision_formula is not None):
        if ('subset' in kwargs):
            d = data.ix[kwargs['subset']]
            Z = patsy.dmatrix(exog_precision_formula, d)
        else:
            Z = patsy.dmatrix(exog_precision_formula, data)
        kwargs['exog_precision'] = Z
    return super(BetaModel, cls).from_formula(formula, data, *args, **kwargs)