code: def test_regression_hdmr_case2():
      problem = {
          "num_vars": 5,
          "names": ["x1", "x2", "x3", "x4", "x5"],
          "bounds": [[0, 1] * 5],
      }
      # Generate correlated samples
      mean = np.zeros((problem["num_vars"]))
      cov = [
          [1, 0.6, 0.2, 0, 0],
          [0.6, 1, 0.2, 0, 0],
          [0.2, 0.2, 1, 0, 0],
          [0, 0, 0, 1, 0.2],
          [0, 0, 0, 0.2, 1],
      ]
      X = np.random.multivariate_normal(mean, cov, 10000)
      Y = linear_model_1.evaluate(X)
      options = {
          "maxorder": 2,
          "maxiter": 100,
          "m": 2,
          "K": 1,
          "R": 10000,
          "alpha": 0.95,
          "lambdax": 0.01,
          "print_to_console": False,
      }
      Si = hdmr.analyze(problem, X, Y, **options)
      assert_allclose(
          Si["Sa"][0 : problem["num_vars"]],
          [0.13] * 5,
          atol=5e-2,
          rtol=1e-1,
      )
      assert_allclose(
          Si["Sb"][0 : problem["num_vars"]],
          [0.11, 0.11, 0.06, 0.03, 0.03],
          atol=5e-2,
          rtol=1e-1,
      )
  
imports: from pytest import fixture, mark
  import numpy
  from numpy.testing import assert_allclose
  from SALib.analyze import delta, dgsm, fast, rbd_fast, sobol, morris, hdmr
  from SALib.sample import fast_sampler, finite_diff, latin, saltelli
  from SALib.sample.morris import sample
  from SALib.test_functions import Ishigami
  from SALib.test_functions import linear_model_1
  from SALib.test_functions import linear_model_2
  from SALib.util import read_param_file
label_desc: Use image node_id 9 for calling a global function with example usage: test_regression_hdmr_case2() without return types