code: def generate_poisson():
      # Regression coefficients
      beta = np.zeros(5, dtype=np.float64)
      beta[2] = 0.5
      beta[4] = -0.5
  
      nclust = 100
  
      OUT = open("gee_poisson_1.csv", "w", encoding="utf-8")
  
      for i in range(nclust):
          n = np.random.randint(3, 6)  # Cluster size
  
          x = np.random.normal(size=(n, 5))
          for j in range(5):
              x[:, j] += np.random.normal()
          lp = np.dot(x, beta)
          E = np.exp(lp)
          y = [np.random.poisson(e) for e in E]
          y = np.array(y)
  
          for j in range(n):
              OUT.write("%d, %d," % (i, y[j]))
              OUT.write(",".join(["%.3f" % b for b in x[j, :]]) + "\n")
  
      OUT.close()
  
file_path: statsmodels/statsmodels/genmod/tests/results/gee_generate_tests.py
imports: import numpy
  from scipy.stats.distributions import norm
label_desc: Use image node_id 6 for calling a global function with example usage: generate_poisson() without return types