original_docstring: 
          Calculates the three-fold Oaxaca Blinder Decompositions
  
          Parameters
          ----------
          std: boolean, optional
              If true, bootstrapped standard errors will be calculated.
          n: int, optional
              A amount of iterations to calculate the bootstrapped
              standard errors. This defaults to 5000.
          conf: float, optional
              This is the confidence required for the standard error
              calculation. Defaults to .99, but could be anything less
              than or equal to one. One is heavy discouraged, due to the
              extreme outliers inflating the variance.
  
          Returns
          -------
          OaxacaResults
              A results container for the three-fold decomposition.
          
docstring: Calculates the three-fold Oaxaca Blinder Decompositions
  Parameters
  
  boolean, optional
  If true, bootstrapped standard errors will be calculated.
  n: int, optional
  A amount of iterations to calculate the bootstrapped
  standard errors. This defaults to 5000.
  conf: float, optional
  This is the confidence required for the standard error
  calculation. Defaults to .99, but could be anything less
  than or equal to one. One is heavy discouraged, due to the
  extreme outliers inflating the variance.
  
  Returns
  
  OaxacaResults
  A results container for the three-fold decomposition.
docstring_tokens: Calculates the three - fold Oaxaca Blinder Decompositions Parameters boolean optional If true bootstrapped standard errors will be calculated . n : int optional A amount of iterations to calculate the bootstrapped standard errors . This defaults to 5000 . conf : float optional This is the confidence required for the standard error calculation . Defaults to . 99 but could be anything less than or equal to one . One is heavy discouraged due to the extreme outliers inflating the variance . Returns OaxacaResults A results container for the three - fold decomposition .
code: def three_fold(self, std=False, n=None, conf=None):
          """
          Calculates the three-fold Oaxaca Blinder Decompositions
  
          Parameters
          ----------
          std: boolean, optional
              If true, bootstrapped standard errors will be calculated.
          n: int, optional
              A amount of iterations to calculate the bootstrapped
              standard errors. This defaults to 5000.
          conf: float, optional
              This is the confidence required for the standard error
              calculation. Defaults to .99, but could be anything less
              than or equal to one. One is heavy discouraged, due to the
              extreme outliers inflating the variance.
  
          Returns
          -------
          OaxacaResults
              A results container for the three-fold decomposition.
          """
          self.submitted_n = n
          self.submitted_conf = conf
          self.submitted_weight = None
          std_val = None
          self.endow_eff = (
              self.exog_f_mean - self.exog_s_mean
          ) @ self._s_model.params
          self.coef_eff = self.exog_s_mean @ (
              self._f_model.params - self._s_model.params
          )
          self.int_eff = (self.exog_f_mean - self.exog_s_mean) @ (
              self._f_model.params - self._s_model.params
          )
  
          if std is True:
              std_val = self.variance(3)
  
          return OaxacaResults(
              (self.endow_eff, self.coef_eff, self.int_eff, self.gap),
              3,
              std_val=std_val,
          )
code_tokens: def three_fold ( self , std = False , n = None , conf = None ) : self . submitted_n = n self . submitted_conf = conf self . submitted_weight = None std_val = None self . endow_eff = ( self . exog_f_mean - self . exog_s_mean ) @ self . _s_model . params self . coef_eff = self . exog_s_mean @ ( self . _f_model . params - self . _s_model . params ) self . int_eff = ( self . exog_f_mean - self . exog_s_mean ) @ ( self . _f_model . params - self . _s_model . params ) if std is True : std_val = self . variance ( 3 ) return OaxacaResults ( ( self . endow_eff , self . coef_eff , self . int_eff , self . gap ) , 3 , std_val = std_val , )
short_docstring: Calculates the three-fold Oaxaca Blinder Decompositions
  Parameters
short_docstring_tokens: Calculates the three - fold Oaxaca Blinder Decompositions Parameters
comment: """
          Calculates the three-fold Oaxaca Blinder Decompositions
  
          Parameters
          ----------
          std: boolean, optional
              If true, bootstrapped standard errors will be calculated.
          n: int, optional
              A amount of iterations to calculate the bootstrapped
              standard errors. This defaults to 5000.
          conf: float, optional
              This is the confidence required for the standard error
              calculation. Defaults to .99, but could be anything less
              than or equal to one. One is heavy discouraged, due to the
              extreme outliers inflating the variance.
  
          Returns
          -------
          OaxacaResults
              A results container for the three-fold decomposition.
          """