def __init__(self):
        # Test Precision
        self.decimal_resid = DECIMAL_1
        self.decimal_params = DECIMAL_3
        self.decimal_resids = -1 # 1 % mismatch at 0
        self.decimal_fittedvalues = DECIMAL_1

        from statsmodels.datasets.committee import load
        self.data = load()
        self.data.exog[:,2] = np.log(self.data.exog[:,2])
        interaction = self.data.exog[:,2]*self.data.exog[:,1]
        self.data.exog = np.column_stack((self.data.exog,interaction))
        self.data.exog = add_constant(self.data.exog, prepend=False)
        self.res1 = GLM(self.data.endog, self.data.exog,
                family=sm.families.NegativeBinomial()).fit()
        from .results.results_glm import Committee
        res2 = Committee()
        res2.aic_R += 2 # They don't count a degree of freedom for the scale
        self.res2 = res2

#    def setup(self):
#        if skipR:
#            raise SkipTest, "Rpy not installed"
#        r.library('MASS')  # this doesn't work when done in rmodelwrap?
#        self.res2 = RModel(self.data.endog, self.data.exog, r.glm,
#                family=r.negative_binomial(1))
#        self.res2.null_deviance = 27.8110469364343

#class TestGlmNegbinomial_log(CheckModelResultsMixin):
#    pass

#class TestGlmNegbinomial_power(CheckModelResultsMixin):
#    pass

#class TestGlmNegbinomial_nbinom(CheckModelResultsMixin):
#    pass

#NOTE: hacked together version to test poisson offset
Read the parameter values for a single stimulus condition.
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/genmod/tests/test_glm.py/TestGlmNegbinomial.__init__--crossover with--dataset/ETHPy150Open NeuralEnsemble/python-neo/neo/io/brainwaref32io.py/BrainwareF32IO.__read_condition