code: def test_boxcox_transformation_methods(self):
      # testing estimated lambda vs. provided. Should result in almost
      # the same transformed data. Value taken from R.
      y_transformed_no_lambda = self.bc.transform_boxcox(self.x)
      y_transformed_lambda = self.bc.transform_boxcox(self.x, 0.507624)
  
      assert_almost_equal(
          y_transformed_no_lambda[0], y_transformed_lambda[0], 3
      )
  
      # a perfectly increasing set has a constant variance over the entire
      # series, hence stabilising should result in the same scale: lmbda = 1.
      y, lmbda = self.bc.transform_boxcox(np.arange(1, 100))
      assert_almost_equal(lmbda, 1.0, 5)
  
file_path: statsmodels/statsmodels/base/tests/test_transform.py
imports: import numpy
  from numpy.testing import assert_almost_equal, assert_equal, assert_raises
  from statsmodels.base.transform import BoxCox
  from statsmodels.datasets import macrodata
label_desc: Use image node_id 9 for calling the TestTransform obj's underlying member method code with example usage: obj.test_boxcox_transformation_methods() without return types