class_docstr: This class summarizes the fit of the OaxacaBlinder model.
  
  Use .summary() to get a table of the fitted values or
  use .params to receive a list of the values
  use .std to receive a list of the standard errors
  
  If a two-fold model was fitted, this will return
  unexplained effect, explained effect, and the
  mean gap. The list will always be of the following order
  and type. If standard error was asked for, then standard error
  calculations will also be included for each variable after each
  calculated effect.
  
  unexplained : float
      This is the effect that cannot be explained by the data at hand.
      This does not mean it cannot be explained with more.
  explained : float
      This is the effect that can be explained using the data.
  gap : float
      This is the gap in the mean differences of the two groups.
  
  If a three-fold model was fitted, this will
  return characteristic effect, coefficient effect
  interaction effect, and the mean gap. The list will
  be of the following order and type. If standard error was asked
  for, then standard error calculations will also be included for
  each variable after each calculated effect.
  
  endowment effect : float
      This is the effect due to the group differences in
      predictors
  coefficient effect : float
      This is the effect due to differences of the coefficients
      of the two groups
  interaction effect : float
      This is the effect due to differences in both effects
      existing at the same time between the two groups.
  gap : float
      This is the gap in the mean differences of the two groups.
  
  Attributes
  ----------
  params
      A list of all values for the fitted models.
  std
      A list of standard error calculations.
class_docstr_tok: ["This","class","summarizes","the","fit","of","the","OaxacaBlinder","model",".","Use",".summary","(",")","to","get","a","table","of","the","fitted","values","or","use",".params","to","receive","a","list","of","the","values","use",".std","to","receive","a","list","of","the","standard","errors","If","a","two-fold","model","was","fitted",",","this","will","return","unexplained","effect",",","explained","effect",",","and","the","mean","gap",".","The","list","will","always","be","of","the","following","order","and","type",".","If","standard","error","was","asked","for",",","then","standard","error","calculations","will","also","be","included","for","each","variable","after","each","calculated","effect",".","unexplained",":","float","This","is","the","effect","that","can","not","be","explained","by","the","data","at","hand",".","This","does","not","mean","it","can","not","be","explained","with","more",".","explained",":","float","This","is","the","effect","that","can","be","explained","using","the","data",".","gap",":","float","This","is","the","gap","in","the","mean","differences","of","the","two","groups",".","If","a","three-fold","model","was","fitted",",","this","will","return","characteristic","effect",",","coefficient","effect","interaction","effect",",","and","the","mean","gap",".","The","list","will","be","of","the","following","order","and","type",".","If","standard","error","was","asked","for",",","then","standard","error","calculations","will","also","be","included","for","each","variable","after","each","calculated","effect",".","endowment","effect",":","float","This","is","the","effect","due","to","the","group","differences","in","predictors","coefficient","effect",":","float","This","is","the","effect","due","to","differences","of","the","coefficients","of","the","two","groups","interaction","effect",":","float","This","is","the","effect","due","to","differences","in","both","effects","existing","at","the","same","time","between","the","two","groups",".","gap",":","float","This","is","the","gap","in","the","mean","differences","of","the","two","groups",".","Attributes","--","--","--","--","--","params","A","list","of","all","values","for","the","fitted","models",".","std","A","list","of","standard","error","calculations","."]
code: def __init__(self, results, model_type, std_val=None):
      self.params = results
      self.std = std_val
      self.model_type = model_type
  
file_path: statsmodels/statsmodels/stats/oaxaca.py
imports: from textwrap import dedent
  import numpy
  from statsmodels.regression.linear_model import OLS
  from statsmodels.tools.tools import add_constant
label_desc: Use image node_id 1 to create a new OaxacaResults object  with example: obj = OaxacaResults(results, model_type, std_val)