class_docstr: The results for the Longley dataset were obtained from NIST
  
  http://www.itl.nist.gov/div898/strd/general/dataarchive.html
  
  Other results were obtained from Stata
class_docstr_tok: ["The","results","for","the","Longley","dataset","were","obtained","from","NIST","http",":","\/\/www.itl.nist.gov\/div898\/strd\/general\/dataarchive.html","Other","results","were","obtained","from","Stata"]
code: def __init__(self):
      self.params = (
          15.0618722713733,
          -0.358191792925910e-01,
          -2.02022980381683,
          -1.03322686717359,
          -0.511041056535807e-01,
          1829.15146461355,
          -3482258.63459582,
      )
      self.bse = (
          84.9149257747669,
          0.334910077722432e-01,
          0.488399681651699,
          0.214274163161675,
          0.226073200069370,
          455.478499142212,
          890420.383607373,
      )
      self.scale = 92936.0061673238
      self.rsquared = 0.995479004577296
      self.rsquared_adj = 0.99246501
      self.df_model = 6
      self.df_resid = 9
      self.ess = 184172401.944494
      self.ssr = 836424.055505915
      self.mse_model = 30695400.3240823
      self.mse_resid = 92936.0061673238
      self.mse_total = (self.ess + self.ssr) / (
          self.df_model + self.df_resid
      )
      self.fvalue = 330.285339234588
      self.llf = -109.6174
      self.aic = 233.2349
      self.bic = 238.643
      self.pvalues = np.array(
          [
              0.86314083,
              0.31268106,
              0.00253509,
              0.00094437,
              0.8262118,
              0.0030368,
              0.0035604,
          ]
      )
      # pvalues from rmodelwrap
      self.resid = np.array(
          (
              267.34003,
              -94.01394,
              46.28717,
              -410.11462,
              309.71459,
              -249.31122,
              -164.04896,
              -13.18036,
              14.30477,
              455.39409,
              -17.26893,
              -39.05504,
              -155.54997,
              -85.67131,
              341.93151,
              -206.75783,
          )
      )
  
      # Obtained from R using
      #  m$residuals / sqrt(sum(m$residuals * m$residuals) / m$df.residual)
      self.resid_pearson = np.array(
          (
              0.87694426,
              -0.30838998,
              0.15183385,
              -1.34528175,
              1.01594375,
              -0.81780510,
              -0.53812289,
              -0.04323497,
              0.04692334,
              1.49381010,
              -0.05664654,
              -0.12811061,
              -0.51024404,
              -0.28102399,
              1.12162357,
              -0.67821900,
          )
      )
  
file_path: statsmodels/statsmodels/regression/tests/results/results_regression.py
imports: import numpy
label_desc: Use image node_id 1 to create a new Longley object  with example: obj = Longley()