class_docstr: Results obtained from Stata 11
class_docstr_tok: ["Results","obtained","from","Stata","11"]
code: def negativebinomial_geometric_bfgs():
      # Smoke tests TODO: Cross check with other stats package
      obj = Namespace()
      obj.nobs = 20190
      obj.params = [
          -0.05768894,
          -0.26646696,
          0.04088528,
          -0.03795503,
          0.26885821,
          0.03802523,
          -0.04308456,
          0.01931675,
          0.18051684,
          0.66469896,
      ]
      obj.bse = [
          0.00553867,
          0.02061988,
          0.00375937,
          0.0030924,
          0.02701658,
          0.00132201,
          0.01821646,
          0.03271784,
          0.06666231,
          0.02250053,
      ]
      obj.pvalues = [
          2.10310916e-025,
          3.34666368e-038,
          1.50697768e-027,
          1.25468406e-034,
          2.48155744e-023,
          6.18745348e-182,
          1.80230194e-002,
          5.54919603e-001,
          6.77044178e-003,
          8.44913440e-192,
      ]
      obj.z = [
          -10.41567024,
          -12.92281571,
          10.8755779,
          -12.27364916,
          9.95160202,
          28.76323587,
          -2.36514487,
          0.59040434,
          2.70792943,
          29.54148082,
      ]
      obj.aic = 87101.159433012392  # old value 87101.160011780419
      obj.bic = 87180.288860125467  # old value 87180.289438893495
      obj.df_model = 9.0
      obj.df_resid = 20180.0
      obj.llf = -43540.58000589021
      obj.llnull = -44586.650971362695  # old value -44199.27443567125
      obj.llr = 2092.1425097129977  # old value 1317.3888595620811
      obj.llr_pvalue = 0  # old value 5.4288002863296022e-278
      obj.fittedvalues = [
          0.89348994,
          0.89348994,
          0.89348994,
          0.89348994,
          0.89348994,
          0.9365745,
          0.9365745,
          0.9365745,
          0.9365745,
          0.9365745,
      ]
      obj.conf_int = [
          [-0.06854453, -0.04683335],
          [-0.30688118, -0.22605273],
          [0.03351706, 0.04825351],
          [-0.04401602, -0.03189404],
          [0.21590669, 0.32180972],
          [0.03543415, 0.04061632],
          [-0.07878816, -0.00738096],
          [-0.04480903, 0.08344253],
          [0.04986111, 0.31117258],
          [0.62059873, 0.70879919],
      ]
      return obj
  
imports: import os
  import numpy
label_desc: Use image node_id 5 for calling the RandHIE obj's underlying member method code with example usage: obj.negativebinomial_geometric_bfgs() and returns: obj