def METHOD_NAME():
    # Number of clusters (clusters have 10 values, partitioned into 2
    # subclusters of size 5).
    nclust = 200
    # Regression coefficients
    beta = np.array([1, -2, 1], dtype=np.float64)
    # Top level cluster variance component
    v1 = 1
    # Subcluster variance component
    v2 = 0.5
    # Error variance component
    v3 = 1.5
    p = len(beta)
    OUT = open("gee_nested_linear_1.csv", "w", encoding="utf-8")
    for i in range(nclust):
        x = np.random.normal(size=(10, p))
        y = np.dot(x, beta)
        y += np.sqrt(v1)*np.random.normal()
        y[0:5] += np.sqrt(v2)*np.random.normal()
        y[5:10] += np.sqrt(v2)*np.random.normal()
        y += np.sqrt(v3)*np.random.normal(size=10)
        for j in range(10):
            OUT.write("%d, %.3f," % (i, y[j]))
            OUT.write(",".join(["%.3f" % b for b in x[j, :]]) + "\n")
    OUT.close()