class_docstr: Use the negative binomial distribution to check GEE estimation
  using the overdispered Poisson model with independent dependence.
  
  Simulating
      X = np.random.negative_binomial(n, p, size)
  then EX = (1 - p) * n / p
       Var(X) = (1 - p) * n / p**2
  
  These equations can be inverted as follows:
  
      p = E / V
      n = E * p / (1 - p)
  
  dparams[0] is the common correlation coefficient
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code: def print_dparams(self, dparams_est):
      OUT.write(
          "Estimated inverse scale parameter:       %8.4f\n"
          % dparams_est[0]
      )
      OUT.write(
          "True inverse scale parameter:            %8.4f\n"
          % self.scale_inv
      )
      OUT.write("\n")
  
file_path: statsmodels/statsmodels/genmod/tests/gee_poisson_simulation_check.py
imports: import numpy
  from statsmodels.genmod.families import Poisson
  from .gee_gaussian_simulation_check import GEE_simulator
  from statsmodels.genmod.generalized_estimating_equations import GEE
  from statsmodels.genmod.cov_struct import Exchangeable, Independence
label_desc: Use image node_id 1 for calling the Overdispersed_simulator obj's underlying member method code with example usage: obj.print_dparams(dparams_est) without return types