content: # -*- coding: utf-8 -*-
  """
  
  Created on Sun Jan 06 09:50:54 2013
  
  Author: Josef Perktold
  """
  
  from __future__ import print_function
  
  if __name__ == '__main__':
  
      import numpy as np
      import matplotlib.pyplot as plt
      from statsmodels.nonparametric.api import KernelReg
      import statsmodels.sandbox.nonparametric.dgp_examples as dgp
  
  
      seed = np.random.randint(999999)
      seed = 430973
      print(seed)
      np.random.seed(seed)
  
      funcs = [dgp.UnivariateFanGijbels1(),
               dgp.UnivariateFanGijbels2(),
               dgp.UnivariateFanGijbels1EU(),
               #dgp.UnivariateFanGijbels2(distr_x=stats.uniform(-2, 4))
               dgp.UnivariateFunc1()
               ]
  
      res = []
      fig = plt.figure()
      for i,func in enumerate(funcs):
          #f = func()
          f = func
          model = KernelReg(endog=[f.y], exog=[f.x], reg_type='ll',
                            var_type='c', bw='cv_ls')
          mean, mfx = model.fit()
          ax = fig.add_subplot(2, 2, i+1)
          f.plot(ax=ax)
          ax.plot(f.x, mean, color='r', lw=2, label='est. mean')
          ax.legend(loc='upper left')
          res.append((model, mean, mfx))
  
      fig.suptitle('Kernel Regression')
      fig.show()
  