code: def setup_class(cls):
      # DGP: simple polynomial
      order = 3
      sigma_noise = 0.5
      nobs = 100
      lb, ub = -1, 2
      cls.x = x = np.linspace(lb, ub, nobs)
      cls.exog = exog = x[:, None] ** np.arange(order + 1)
      y_true = exog.sum(1)
      np.random.seed(987567)
      cls.y = y = y_true + sigma_noise * np.random.randn(nobs)
  
imports: import numpy
  from numpy.testing import assert_almost_equal, assert_equal
  from statsmodels.sandbox.nonparametric import smoothers
  from statsmodels.regression.linear_model import OLS, WLS
label_desc: Use image node_id 1 for calling the BasePolySmoother obj's underlying member method code with example usage: obj.setup_class(cls) without return types