new_contents: # -*- coding: utf-8 -*-
  """
  
  Created on Thu Jul 18 14:57:46 2013
  
  Author: Josef Perktold
  """
  
  import numpy as np
  
  from statsmodels.genmod.generalized_estimating_equations import GEE, GEEMargins
  
  from statsmodels.genmod.families import Gaussian, Binomial, Poisson
  from statsmodels.genmod.dependence_structures import (Exchangeable,
      Independence, GlobalOddsRatio, Autoregressive, Nested)
  
  from statsmodels.genmod.tests import gee_gaussian_simulation_check as gees
  
  da,va = gees.gen_gendat_ar0(0.6)()
  ga = Gaussian()
  lhs = np.array([[0., 1, 1, 0, 0],])
  rhs = np.r_[0.,]
  md = GEE(da.endog, da.exog, da.group, da.time, ga, va,
                   constraint=(lhs, rhs))
  mdf = md.fit()
  print mdf.summary()
  
  
  md2 = GEE(da.endog, da.exog, da.group, da.time, ga, va,
                   constraint=None)
  mdf2 = md2.fit()
  print '\n\n'
  print mdf2.summary()
  
  
  mdf2.use_t = False
  mdf2.model.df_resid = np.diff(mdf2.model.exog.shape)
  print mdf2.t_test(np.eye(len(mdf2.params)))
  # need master to get wald_test
  #print mdf2.wald_test(np.eye(len(mdf2.params))[1:])
  
  '''
  >>> mdf2.predict(da.exog.mean(0))
  Traceback (most recent call last):
    File "<pyshell#11>", line 1, in <module>
      mdf2.predict(da.exog.mean(0))
    File "e:\josef\eclipsegworkspace\statsmodels-git\statsmodels-all-new2_py27\statsmodels\statsmodels\base\model.py", line 963, in predict
      return self.model.predict(self.params, exog, *args, **kwargs)
    File "e:\josef\eclipsegworkspace\statsmodels-git\statsmodels-all-new2_py27\statsmodels\statsmodels\genmod\generalized_estimating_equations.py", line 621, in predict
      fitted = offset + np.dot(exog, params)
  TypeError: unsupported operand type(s) for +: 'NoneType' and 'numpy.float64'
  '''
  mdf2.predict(da.exog.mean(0), offset=0)
  # -0.10867809062890971
  
  marg = GEEMargins(mdf, ())
  print marg.summary()
  
subject: add my try_gee script