class_docstr: GMM class to get cov_params for treatment effects
  
  This combines moment conditions for the selection/treatment model and the
  outcome model to get the standard errors for the treatment effect that
  takes the first step estimation of the treatment model into account.
  
  this also matches standard errors of ATE and POM in Stata
class_docstr_tok: ["GMM","class","to","get","cov_params","for","treatment","effects","This","combines","moment","conditions","for","the","selection\/treatment","model","and","the","outcome","model","to","get","the","standard","errors","for","the","treatment","effect","that","takes","the","first","step","estimation","of","the","treatment","model","into","account",".","this","also","matches","standard","errors","of","ATE","and","POM","in","Stata"]
code: def __init__(
      self,
      endog,
      res_select,
      mom_outcome,
      exclude_tmoms=False,
      **kwargs,
  ):
      super().__init__(endog, None, None)
      self.results_select = res_select
      self.mom_outcome = mom_outcome
      self.exclude_tmoms = exclude_tmoms
      self.__dict__.update(kwargs)
  
      # add xnames so it's not None
      # we don't have exog in init in this version
      if self.data.xnames is None:
          self.data.xnames = []
  
      # need information about decomposition of parameters
      if exclude_tmoms:
          self.k_select = 0
      else:
          self.k_select = len(res_select.model.data.param_names)
  
      if exclude_tmoms:
          # fittedvalues is still linpred
          self.prob = self.results_select.predict()
      else:
          self.prob = None
  
imports: import numpy
  from statsmodels.compat.pandas import Substitution
  from scipy.linalg import block_diag
  from statsmodels.regression.linear_model import WLS
  from statsmodels.sandbox.regression.gmm import GMM
  from statsmodels.stats.contrast import ContrastResults
  from statsmodels.tools.docstring import indent
label_desc: Use image node_id 1 to create a new _TEGMMGeneric1 object from inherited base classes: GMM with example: obj = _TEGMMGeneric1(endog, res_select, mom_outcome, exclude_tmoms)