code: def generate_nominal():
      # Regression coefficients
      beta1 = np.r_[0.5, 0.5]
      beta2 = np.r_[-1, -0.5]
      p = len(beta1)
  
      rz = 0.5
  
      OUT = open("gee_nominal_1.csv", "w", encoding="utf-8")
  
      for i in range(200):
          n = np.random.randint(3, 6)  # Cluster size
  
          x = np.random.normal(size=(n, p))
          x[:, 0] = 1
          for j in range(1, x.shape[1]):
              x[:, j] += np.random.normal()
          pr1 = np.exp(np.dot(x, beta1))[:, None]
          pr2 = np.exp(np.dot(x, beta2))[:, None]
          den = 1 + pr1 + pr2
          pr = np.hstack((pr1 / den, pr2 / den, 1 / den))
          cpr = np.cumsum(pr, 1)
  
          z = rz * np.random.normal() + np.sqrt(
              1 - rz**2
          ) * np.random.normal(size=n)
          u = norm.cdf(z)
  
          y = (u[:, None] > cpr).sum(1)
  
          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 5 for calling a global function with example usage: generate_nominal() without return types