class_docstr: Results for EL Regression
class_docstr_tok: ["Results","for","EL","Regression"]
code: def __init__(self):
      self.source = "Matlab"
      self.test_beta0 = (
          1.758104,
          0.184961,
          np.array(
              [
                  0.04326392,
                  0.04736749,
                  0.03573865,
                  0.04770535,
                  0.04721684,
                  0.04718301,
                  0.07088816,
                  0.05631242,
                  0.04865098,
                  0.06572099,
                  0.04016013,
                  0.04438627,
                  0.04042288,
                  0.03938043,
                  0.04006474,
                  0.04845233,
                  0.01991985,
                  0.03623254,
                  0.03617999,
                  0.05607242,
                  0.0886806,
              ]
          ),
      )
  
      self.test_beta1 = (
          1.932529,
          0.164482,
          np.array(
              [
                  0.033328,
                  0.051412,
                  0.03395,
                  0.071695,
                  0.046433,
                  0.041303,
                  0.033329,
                  0.036413,
                  0.03246,
                  0.037776,
                  0.043872,
                  0.037507,
                  0.04762,
                  0.04881,
                  0.05874,
                  0.049553,
                  0.048898,
                  0.04512,
                  0.041142,
                  0.048121,
                  0.11252,
              ]
          ),
      )
  
      self.test_beta2 = (
          0.494593,
          0.481866,
          np.array(
              [
                  0.046287,
                  0.048632,
                  0.048772,
                  0.034769,
                  0.048416,
                  0.052447,
                  0.053336,
                  0.050112,
                  0.056053,
                  0.049318,
                  0.053609,
                  0.055634,
                  0.042188,
                  0.046519,
                  0.048415,
                  0.047897,
                  0.048673,
                  0.047695,
                  0.047503,
                  0.047447,
                  0.026279,
              ]
          ),
      )
  
      self.test_beta3 = (
          3.537250,
          0.060005,
          np.array(
              [
                  0.036327,
                  0.070483,
                  0.048965,
                  0.087399,
                  0.041685,
                  0.036221,
                  0.016752,
                  0.019585,
                  0.027467,
                  0.02957,
                  0.069204,
                  0.060167,
                  0.060189,
                  0.030007,
                  0.067371,
                  0.046862,
                  0.069814,
                  0.053041,
                  0.053362,
                  0.041585,
                  0.033943,
              ]
          ),
      )
  
      self.test_ci_beta0 = (-52.77128837058528, -24.11607348661947)
  
      self.test_ci_beta1 = (0.41969831751229664, 0.9857167306604057)
  
      self.test_ci_beta2 = (0.6012045929381431, 2.1847079367275692)
  
      self.test_ci_beta3 = (-0.3804313225443794, 0.006934528877337928)
  
file_path: statsmodels/statsmodels/emplike/tests/results/el_results.py
imports: import numpy
label_desc: Use image node_id 1 to create a new RegressionResults object  with example: obj = RegressionResults()