code: def test_tricube():
      # > library(kedd)
      # > xx = c(-1., -0.75, -0.5, -0.25, 0., 0.25, 0.5, 0.75, 1.)
      # > res = kernel.fun(x = xx, kernel="tricube",deriv.order=0)
      # > res$kx
  
      res_kx = [
          0.0000000000000000,
          0.1669853116259163,
          0.5789448302469136,
          0.8243179321289062,
          0.8641975308641975,
          0.8243179321289062,
          0.5789448302469136,
          0.1669853116259163,
          0.0000000000000000,
      ]
      xx = np.linspace(-1, 1, 9)
      kx = kernels.Tricube()(xx)
      assert_allclose(kx, res_kx, rtol=1e-10)
  
imports: import os
  import numpy
  from numpy.testing import assert_allclose, assert_array_less
  import pandas
  import pytest
  from statsmodels.sandbox.nonparametric import kernels
label_desc: Use image node_id 1 for calling a global function with example usage: test_tricube() without return types