class_docstr: Results obtained from Stata 11
class_docstr_tok: ["Results","obtained","from","Stata","11"]
code: def generalizedpoisson_gp2():
      # Stata gnpoisson function
      obj = Namespace()
      obj.nobs = 20190
      obj.llf = -43326.42720093228
      obj.params = [
          -0.0604495342,
          -0.277717228,
          0.0438136144,
          -0.0395811744,
          0.273044906,
          0.0399108677,
          -0.0552626543,
          -0.001227569488,
          0.151980519,
          0.651125316,
          0.448085318,
      ]
      obj.lnalpha_std_err = 0.0125607
      obj.lnalpha = -0.8027716
      obj.bse = [
          0.00634704,
          0.02381906,
          0.00443871,
          0.00355094,
          0.0334247,
          0.00166303,
          0.02102142,
          0.0390845,
          0.087821,
          0.02626823,
          0.00562825,
      ]
      obj.df_model = 9
      obj.aic = 86674.854401865
      obj.conf_int = [
          [-0.07288951, -0.04800956],
          [-0.32440173, -0.23103272],
          [0.03511389, 0.05251333],
          [-0.04654088, -0.03262147],
          [0.20753371, 0.33855610],
          [0.03665139, 0.04317034],
          [-0.09646387, -0.01406144],
          [-0.07783191, 0.07537652],
          [-0.02014548, 0.32410651],
          [0.59964053, 0.70261011],
          [0.43718883, 0.45925338],
      ]
      obj.bic = 86761.896771689
      obj.wald_pvalue = 4.8795019354e-254
      obj.wald_statistic = 1206.46339591254
      return obj
  
imports: import os
  import numpy
label_desc: Use image node_id 6 for calling the RandHIE obj's underlying member method code with example usage: obj.generalizedpoisson_gp2() and returns: obj